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In this paper, we present a novel pseudo sequence based 2-D hierarchical reference structure for light-field image compression. In the proposed scheme, we first decompose the light-field image into multiple views and organize them into a 2-D coding structure according to the spatial coordinates of the corresponding microlens. Then we mainly develop three technologies to optimize the 2-D coding structure. First, we divide all the views into four quadrants, and all the views are encoded one quadrant after another to reduce the reference buffer size as much as possible. Inside each quadrant, all the views are encoded hierarchically to fully exploit the correlations between different views. Second, we propose to use the distance between the current view and its reference views as the criteria for selecting better reference frames for each inter view. Third, we propose to use the spatial relative positions between different views to achieve more accurate motion vector scaling. The whole scheme is implemented in the reference software of High Efficiency Video Coding. The experimental results demonstrate that the proposed novel pseudo-sequence based 2-D hierarchical structure can achieve maximum 14.2% bit-rate savings compared with the state-of-the-art light-field image compression method.

Most existing audio steganographic methods embed secret messages according to a pseudorandom number generator, thus some auditory sensitive parts in cover audio, such as mute or near-mute segments, will be contaminated, which would lead to poor perceptual quality and may introduce some detectable artifacts for steganalysis. In this paper, we propose a novel adaptive audio steganography in the time domain based on the advanced audio coding (AAC) and the Syndrome-Trellis coding (STC). The proposed method firstly compresses a given wave signal into AAC compressed file with a high bitrate, and then obtains a residual signal by comparing the signal before and after AAC compression. According to the quantity and sign of the residual signal, \(\pm 1\) embedding costs are assigned to the audio samples. Finally, the STC is used to create the stego audio. The extensive results evaluated on 10,000 music and 10,000 speech audio clips have shown that our method can significantly outperform the conventional \(\pm 1\) LSB based steganography in terms of security and audio quality.

Signals which are sufficiently stationary permit highly efficient coding in the frequency domain. Such signals include speech signals such as sustained vowels and prolonged fricatives, as well as generic audio signals such as music and mixed material. The main components of frequency domain coding methods include windowing, a time-frequency transform, perceptual modelling and entropy coding of the spectral components. This chapter gives an overview of such transform domain coding methods.

In recent years the satellite communication has been growing for the development of rapid and efficient techniques for the storage and transmission of satellite images. The science of reducing the number of bits required to represent the image is called image compression. The aim of this paper is to reduce the size of the image, while transmitting the original image. This reduced image is called as compressed image. The compressed image is being transmitted and it is reconstructed in the receiving side so that the compressed image is being decompressed to obtain the original image. And also transmission of such satellite image increases communication accuracy but requires less bandwidth. In most systems, the amount of intimation that the user wishes to communicate or store necessities some form of compression for efficient and reliable use of communication or storage system. Although several well-known compression techniques exist, many of them require computationally intensive algorithm. In addition to that many compression techniques introduce unwanted attribute such as loss of intimation. This is a major problem in satellite imaging where image degradation may be critical. By considering the above, this paper is to use the wavelet to improve the compression ratio as well as visual quality which is implemented by the famous algorithm called sub band coding and decoding algorithm in MATLAB 7.1 software tool.

A novel and universal coding artifact reduction method is introduced.The coding artifact reduction is viewed as coding loss recovery.The coding loss is recovered from the compressed signal.Experimental results on four codecs demonstrate the effectiveness. Coding artifacts are annoying in highly compressed signals. Most of the existing artifact reduction methods are designed for one specific type of artifacts, codecs, and bitrates, which are complex and exclusive for one type of artifact reduction. Since both the compressed image/video and the coding error contain information of the original signal, they are highly correlated. Therefore, we try to recover some lost data based on the correlation between the compressed signal and the coding error, and introduce a novel and universal artifact reduction method. Firstly, according to the spatial correlation among pixels, a pixel-adaptive anisotropic filter is designed to reconstruct the distorted signal. Next, a globally optimal filter is designed to further recover the coding loss. Experimental results demonstrate that within an extensive range of bitrates, the proposed method achieves about 0.8dB, 0.45dB, 0.3dB, and 0.2dB on average of PSNR improvement for JPEG, MPEG4, H.264/AVC, and HEVC compressed signals, respectively.

This paper presents an advanced screen content coding solution using color table and index map (cTIM) method. This cTIM scheme is implemented in the range extensions of high-efficiency video coding (HEVC-RExt) as an additional tool of intracoding to complement conventional spatial angular prediction to better exploit the screen content redundancy. For each coding unit, a number of major colors will be selected to form the color table, then the original pixel block is translated to the corresponding index map. A 1D or hybrid 1D/2D string match scheme is introduced to derive matched pairs of index map for better compression. Leveraging the color distribution similarity between neighboring image blocks, color table merge is developed to carry it implicitly. For those blocks that color table has to be signaled explicitly, intertable color sharing and intratable color differential predictive coding are applied to reduce the signaling overhead. Extensive experiments have been performed and they have demonstrated the significant coding efficiency improvement over conventional HEVC-RExt, resulting in 26%, 18%, and 15% bit rate reduction at lossless case and 23%, 19%, and 13% Bjontegaard Delta-rate improvement at lossy scenario of typical screen content with text and graphics, for respective all intra, random access, and low-delay using B picture encoder settings. Detailed performance study and complexity analysis (as well as the comparison with other algorithms) have been included as well to evidence the efficiency of proposed algorithm.

A new lossless image coding method competitive with the best known image coding techniques in terms of efficiency and complexity is suggested. It is based on adaptive color space transform, adaptive context coding, and improved prediction of pixel values of image color components. Examples of application of the new algorithm to a set of standard images are given and comparison with known algorithms is performed.

In this paper, a distributed image coding scheme for multi-view video through an efficient generation of side information is proposed. A distributed video coding technique corrects the errors in the side information, which is generated with the original image, by using the channel coding technique at the decoder. Therefore, the more correct the generated side information is, the better the performance of distributed video coding. The proposed technique is to apply the distributed video coding schemes to the image coding for multi-view video. It generates side information by selectively and efficiently using both 3-dimensional warping based on the depth map with spatially adjacent frames and motion-compensated temporal interpolation with temporally adjacent frames. In this scheme the difference between the adjacent frames, the sizes of the motion vectors for the adjacent blocks, and the edge information are used as the selection criteria. From the experiments, it was observed that the quality of the side information generated by the proposed technique was improved by the average peak signal-to-noise ratio of 0.97dB than the one by motion-compensated temporal interpolation or 3-dimensional warping. The result from analyzing the rate-distortion curves revealed that the proposed scheme could reduce the bit-rate by 8.01% on average at the same peak signal-tonoise ratio value, compared to previous work.

Screen content like cartoons, captures of typical computer screens or video with text overlay or news ticker is an important category of video, which needs new techniques beyond the existing video coding techniques. In this paper, we analyze the characteristics of screen content and coding efficiency of HEVC on screen content. We propose a new coding scheme, which adopts a non-transform representation, separating screen content into color component and structure component. Based on the proposed representation, two coding modes are designed for screen content to exploit the directional correlation and non-translational changes in screen video sequences. The proposed scheme is then seamlessly incorporated into the HEVC structure and implemented into HEVC range extension reference software HM9.0. Experimental results show that the proposed scheme achieves up to 52.6% bitrate saving compared with HM9.0. On average, 35.1%, 29.2% and 23.6% bitrate saving are achieved with intra, random-access and low-delay configurations, respectively. The visual quality of the decoded video sequences is also significantly improved by reducing ringing artifacts around sharp edges and reserving the shape of text without blur.

Transform has been widely used to remove spatial redundancy of prediction residuals in the modern video coding standards. However, since the residual blocks exhibit diverse characteristics in a video sequence, conventional transform methods with fixed transform kernels may result in low efficiency. To tackle this problem, we propose a novel content adaptive transform framework for the H.264/AVC-based video coding. The proposed method utilizes pixel rearrangement to dynamically adjust the transform kernels to adapt to the video content. In addition, unlike the traditional adaptive transforms, the proposed method obtains the transform kernels from the reconstructed block, and hence it consumes only one logic indicator for each transform unit. Moreover, a spiral-scanning method is developed to reorder the transform coefficients for better entropy coding. Experimental results on the Key Technical Area (KTA) platform show that the proposed method can achieve an average bitrate reduction of about 7.95% and 7.0% under all-intra and low-delay configurations, respectively.

Reconstruction of the Sparse signal such as for audio signal,video signal, image signal is the major important role.We are going to recover the signal for the audio signal. The signal is recovered by using two algorithm such as AMP-M and AMP-T. These two algorithm coding are written in matlab and simulation from simulink will be used to get the specific outputs. AMP-M used as multiply accumulate unit for the recovery of unstructured matrices. AMP-T used as the fast linear transform. Hence recovery of the Sparse signal with the two algorithm is the main aim of the project .According to the research we have two technique to reconstruct the audio signal like compressive sensing, building of the FPGA hardware but in our project new technique is introduced to recover the audio signal by using two algorithms such as AMP-M and AMP-T .

B-splines caught interest of many engineering applications due to their merits of being flexible and provide a large degree of differentiability and cost/quality trade-off relationship. However, they have less impact with continuous-time applications as they are constructed from piecewise polynomials. On the other hand, exponential spline polynomials (E-splines) represent the best smooth transition between continuous and discrete domains as they are made of exponential segments. In this paper, we present a complete analysis for an E-spline-based subband coding (wavelet) perfect reconstruction (PR) system. Derivations for the scaling and wavelet functions are presented, along with application of the proposed system in image compression and image denoising. In image compression, a comparison of the proposed technique compared with the B-spline-based PR system as well as the basic wavelet subband system with the SPIHT image codec is presented. In image denoising, we report the enhancement achieved with the proposed E-spline-based denoising approach compared with B-spline-based denoising and another basic denoising technique. In both applications, E-splines show superior performance as will be illustrated.

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

In this letter, multiple forward and inverse fast algorithm based transforms and their hardware-sharing design for 2 × 2, 4 × 4, and 8 × 8 transforms in H.264/AVC, and the 8 × 8 transform in audio video coding standard, 4 × 4 and 8 × 8 transforms in VC-1, and DCT/IDCT in MPEG-1/2/4 are developed with a low hardware cost for multistandard video coding applications. Compared with the directly combined fast transforms without shares, the proposed low-cost 1-D architecture reduces shifters by 67%, adders by 73%, and gate counts by 53.4%. The hardware-sharing efficiencies of shifters and adders in the proposed 1-D transform design are 32% and 25% more than those in the previous design, respectively. By 0.18-μm CMOS technology, the proposed 2-D transform architecture has less normalized power per mode and larger normalized hardware efficiency than the previous multiple-standard designs. The cost-effective 2-D full pipelined transform achieves multistandard real-time 1080HD at 60-Hz video encoding and decoding applications.

Video compression coding technology is the key to implement network video transmission, and the increasing requirements of network content transmission quality accelerate the development of video compression coding technology. H.264 is a highly compressed digital video codec standard, and is a hybrid coding mode of differential pulse code modulation (DPCM) and transform encoding. In this paper, we introduced several techniques of hybrid coding algorithm based on H.264 standard, including differential coding, block matching motion prediction method, normalization criteria, variable-size block motion compensation, and multiple hypothesis motion compensation. We did extensive experiments on variable-size block motion compensation coding method. The experimental results show that, with the premise of the 1/4 pixel motion compensation accuracy and hybrid coding, 8 × 8 or larger block partition of content for normal video object, can further make use of space correlation and improve compression efficiency.

Non-reference P frame coding is used to enhance coding efficiency in low-delay encoding configuration of Internet Video Coding (IVC), which is being standardized as a royalty-free video codec in MPEG. The existing method of non-reference P frame coding which was adopted in the reference Test Model of IVC (ITM) 4.0 adaptively applies a non-reference P frame with a fixed coding structure based on the magnitude of motion vectors (MVs), however, which unexpectedly degrades the coding efficiency for some sequences. In this paper, the existing non-reference P frame coding is improved by changing non-reference P frame coding structure and applying a new adaptive method using the ratio of the amount of generated bits of non-reference frames to that of reference frames as well as MVs. Experimental results show that the proposed non-reference P frame coding gives 6.6% BD-rate bit saving in average over ITM 7.0.

Different from the previous video coding standards that employ fixed-size coding blocks (and macroblocks), the latest high efficiency video coding (HEVC) introduces a quadtree structure to represent variable-size coding blocks in the coding loop. The main objective of this study is to investigate a novel way to reuse these variable-size blocks to represent the foreground objects in the picture. Towards this end, this paper proposes three methods, i.e., flagging the blocks lying in the object regions flagging compression blocks (FCB), adding an object tree in each Coding Tree Unit to describe the objects' shape in it additional object tree (AOT) and confining the block splitting procedure to fit the object shape confining by shape (CBS). Among them, FCB and CBS add a flag bit in the syntax description of the block to indicate whether it lies in the objects region, while AOT adds a separate quadtree to represent the objects. For all these methods, the additional bits are then fed into the HEVC entropy coding module to compress. As such, the representation of visual objects in the pictures can be implemented in the HEVC coding loop by reusing the variable-size blocks and entropy coding, without additional coding tools. The experiments on six manually-segmented HEVC testing sequences (three in 1080P and three in 720P) demonstrate the feasibility and effectiveness of our proposal. To represent the objects in the 1080P testing sequences, the BD rate increases of FCB, AOT, and CBS over the HEVC anchor are 1.57%, 3.27%, and 5.93% respectively; while for the 720P conference videos, those are 4.57%, 17.23%, and 26.93% (note that the average bitrate of the anchor is only 1009 kb/s).

Recently, color plus depth map format 3-D video has been introduced as a new 3-D scene representation format, which gains the attention for its relatively low storage and transmission bandwidth requirement in comparison to the multiview video system. Usually, encoding of the color video and the depth data uses two traditional H.264 encoders. The complexity and hardware requirements to code one 2-D view and its associated depth data are nearly two times higher than coding one 2-D view. In this paper, we address the reduction of complexity of depth coding. Since both color videos and depth maps represent the same scene at the same time instant, it is likely for each macroblock to have similar coding information including the prediction mode and motion vectors. Taking advantage of correlations between coding information from depth maps and color videos, we propose a low complexity depth coding algorithm incorporating a fast motion search method and a fast mode decision method. Results show that the proposed algorithm reduces 80% computational complexity with a negligible loss of coding efficiency in comparison with the original Joint Multiview Video Coding encoder.

The accuracy of the side information (SI) is critical in the performance of distributed video coding algorithms. The SI is typically built at a decoder based on the reconstructed data and on channel coding parity bits transmitted by the encoder. The optimal encoding rate is generally difficult to compute precisely due to the dynamics of video content with varying correlation. Effective methods for the refinement of imprecise SI are therefore important for improved decoding quality. In this paper, we propose to exploit the intrinsic property of channel coding algorithms in Wyner-Ziv video coding. The SI is refined via both the information-plane and the parity-plane bits, which rapidly increases the accuracy of refined SI. We use extrinsic information transfer chart analysis in order to estimate the variations of the mutual information in the iterative decoding. In particular, we characterize mutual information variations for punctured regular and irregular rate-compatible low-density parity-check codes. Tracking the mutual information changes permits to decrease the coding rate of the information and parity bitstreams, while preserving the decoding quality. Simulation results confirm that our method improves on the decoding quality of recent distributed video coding algorithms, especially for high-motion sequences or at high-coding rate regimes.

In region-of-interest (ROI)-based video coding, ROI parts of the frame are encoded with higher quality than non-ROI parts. At low bit rates, such encoding may produce attention-grabbing coding artifacts, which may draw viewer's attention away from ROI, thereby degrading visual quality. In this paper, we present a saliency-aware video compression method for ROI-based video coding. The proposed method aims at reducing salient coding artifacts in non-ROI parts of the frame in order to keep user's attention on ROI. Further, the method allows saliency to increase in high quality parts of the frame, and allows saliency to reduce in non-ROI parts. Experimental results indicate that the proposed method is able to improve visual quality of encoded video relative to conventional rate distortion optimized video coding, as well as two state-of-the art perceptual video coding methods.

In this study, the performance of hierarchical transform coding is analysed with design of an order-16 integer transform kernel. The proposed hierarchical transform-coding structure is constructed with a set of 4 × 4, 8 × 8 and 16 × 16 integer transforms of variable transform block sizes, which takes the advantages of both lower and higher transform kernels by flexibly adapting to varying image characteristics of video sequences with homogeneous and complex regions. The proposed hierarchical transform-coding structure is implemented as an extension to H.264/advanced video coding joint model. The authors show the effectiveness of the hierarchical variable-sized block transform scheme by analysing the quantisation effects and the correlation among neighbouring pixels in video sequences of different spatial resolutions. The experimental results show that: (i) the variable-sized block transform scheme with the hierarchical structure is advantageous to the texture regions with strong local edges and (ii) the higher-order-16 integer transform kernel itself is more effective for the homogeneous texture regions, which are often encountered in higher resolution sequences. Therefore these two features can complementarily work in an rate-distortion (RD) optimised manner for various characteristics of the input signals.

In our work we present multiple description coding (MDC) scheme using contourlet transform (CT) for gray scale image. The principle is to prove performance of our algorithm in the coding field in contrast of wavelet that is widely used for image coding. The goal of our approach is to encode directional subbands resulting from the directional stage decomposition, to form the descriptions compressed and transmitted over different channels. The main objective of this work is to encode the source into four descriptions for transmission over packet loss channels, Most of multiple description scenarios are implemented in transform domain. A controlled amount of correlation is appended to the formed descriptions using a pairwise correlating transform (PCT). The experimental results of CT compared to discret wavelet transform (DWT) show that our method achieves better performance in term of delivered peak signal to noise ratio (PSNR) and visual image quality reconstruction.

A novel transform method providing a regionally structured sparse model of residue for a video coding is proposed. Conventional learning-based video coding methods consider only the number of transformed coefficients in a dictionary construction but disregard any structural form of residue. A structural form of coefficients is used for another factor, specified by a set of local block patterns, in a transform design so as to yield the regionally compact distribution of the coefficients. A transform coefficient coding method is also developed because the distribution of the coefficients is different with that of conventional transforms. It is demonstrated with experiments that the proposed method outperforms the coding efficiency and visual quality over high efficiency video coding/screen content coding reference software.

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform scalar deadzone quantization (USDQ) together with a bitplane coding strategy. This paper introduces a 2-step scalar deadzone quantization (2SDQ) scheme that achieves same coding performance as that of USDQ while reducing the coding passes and the emitted symbols of the bitplane coding engine. This serves to reduce the computational costs of the codec and/or to code high dynamic range images. The main insights behind 2SDQ are the use of two quantization step sizes that approximate wavelet coefficients with more or less precision depending on their density, and a rate-distortion optimization technique that adjusts the distortion decreases produced when coding 2SDQ indexes. The integration of 2SDQ in current codecs is straightforward. The applicability and efficiency of 2SDQ are demonstrated within the framework of JPEG2000.

This paper provides an overview of the mode dependent coding tools in the development of video coding technology. In video coding, the prediction mode is closely related with the local image statistical characteristics. For instance, the angular intra mode contains the oriented structure information and the interpartition mode can reveal the local texture properties. Characterized by this fact, the prediction mode can be employed to facilitate the further encoding process, such as transform and coefficient coding. Recently, many mode dependent coding tools were proposed to provide more flexibility and thereby improve the compression performance. In general, these coding tools can be classified into three categories: mode dependent transform, residual reorder before transformation and coefficient scan after transformation. In this paper, these advanced coding algorithms are detailed and experiments are conducted to demonstrate their superior compression performance.

This paper presents a mixed framework based on an efficient intra key frame coding and an improved side information (SI) generation scheme in transform domain Wyner–Ziv (WZ) video coding. The performance of the WZ video coding strongly depends on the quality of the SI. The SI can be generated from the decoded key frames resulted from intra key frame video coding. The better the decoded key frames are the better would be the SI generation. In this paper, a Burrows–Wheeler transform (BWT) based intra-frame video coding is proposed to generate improved decoded key frames. Furthermore, an improved SI generation scheme with multilayer perceptron (MLP) is proposed. Comparative analysis with other standard techniques of WZ video coding reveals that the proposed scheme has better standing as compared to its counterparts in terms of both coding efficiency and improved perceptual quality.

In this paper, we present a new sinusoidal coding and spectral band replication (SBR) method for a low bit-rate super-wideband speech and audio coding. The sinusoidal coding algorithm utilizes the local rms energy of partial frequency bands in modified discrete cosine transform (MDCT) domain to select peak MDCTs. The SBR is based on the pseudo-spectral correlation between lower band and higher band. The proposed techniques are shown experimentally to give improved performance compared to ITU-T G.718 Annex B from the objective and subjective evaluation.

During the last two decades, there has been substantial progress in multirate digital filters and filter banks. This includes the design of quadrature mirror filters (QMF). A two-channel QMF bank is extensively used in many signal processing fields such as subband coding of speech signal, image processing, antenna systems, design of wavelet bases, and biomedical engineering and in digital audio industry. Therefore, new efficient design techniques are being proposed by several authors in this area. This paper presents an overview of analysis and design techniques of the two-channel QMF bank. Application in the area of subband coding and future research trends are also discussed.

This paper describes an extension of the high efficiency video coding (HEVC) standard for coding of multi-view video and depth data. In addition to the known concept of disparity-compensated prediction, inter-view motion parameter, and inter-view residual prediction for coding of the dependent video views are developed and integrated. Furthermore, for depth coding, new intra coding modes, a modified motion compensation and motion vector coding as well as the concept of motion parameter inheritance are part of the HEVC extension. A novel encoder control uses view synthesis optimization, which guarantees that high quality intermediate views can be generated based on the decoded data. The bitstream format supports the extraction of partial bitstreams, so that conventional 2D video, stereo video, and the full multi-view video plus depth format can be decoded from a single bitstream. Objective and subjective results are presented, demonstrating that the proposed approach pro vides 50% bit rate savings in comparison with HEVC simulcast and 20% in comparison with a straightforward multi-view extension of HEVC without the newly developed coding tools.

With the development of modern signal processing technology, the method of Wavelet Transform (WT) has been greatly used in image and video processing. In this paper, a method to use Discrete Wavelet Transform (DWT) in intra-frame (I-frame) video compression is proposed for the purpose of better compression efficiency and quality on the basis of good visual effects. The method can be functioned as a preprocessing of I-frame coding. The experimental results show that the proposed method has an increase in both coding efficiency and quality.

A multiplierless architecture based on algebraic integer representation for computing the Daubechies 4-tap wavelet transform for 1-D/2-D signal processing is proposed. This architecture improves on previous designs in a sense that it minimizes the number of parallel 2-input adder circuits. The algorithm was achieved using numerical optimization based o exhaustive search over the algebraic integer representation. The proposed architecture furnishes exact computation up to the final reconstruction step, which is the operation that maps the exactly computed filtered results from algebraic integer representation to fixed-point. Compared to Madishetty et al. (IEEE Trans Circuits Syst I (Accepted, In Press), 2012a), this architecture shows a reduction of $$10\cdot n-3$$ 10 · n - 3 adder circuits, where $$n$$ n is the number of wavelet decomposition levels. Standard $$512\times 512$$ 512 × 512 images Mandrill, Lena, and Cameraman were submitted to digital realizations of both proposed algebraic integer based as well as fixed-point schemes, leading to quantifiable comparisons. The design is physically implemented for a 4-level 2-D decomposition using a Xilinx Virtex-6 vcx240t-1ff1156 FPGA device operating at up to a maximum clock frequency of 263.15 MHz. The FPGA implementation is tested using hardware co-simulation using an ML605 board with clock of 100 MHz. A 45 nm CMOS synthesis shows improved clock frequency of better than 500 MHz for a supply voltage of 1.1 V.

With the advancement in the video compression and internet technology, the application of video streaming has increased. Because of different types of devices used for accessing the video application and the heterogeneous nature of the network the scalable video coding has become important in order to fulfill the needs of the user. Discrete wavelet transform (DWT) is best tool for scalable video coding because of its property of multiresolution. The coding and display order of pictures in H.264/MPEG4-AVC is completely decoupled and any picture can be marked as reference picture and is used for prediction of following picture independent of corresponding slice type. A wavelet based hierarchical coding structure has been proposed which selects best matched reference frame for the current frame to be encoded based on the mean square error (MSE) in the group of picture(GOP). The scalable encoding of hierarchical prediction has also been exploited. This algorithm has been compared with the performance of traditional multiresolution motion estimation technique based on peak signal to noise ratio. The proposed algorithm show an improvement of 13% in PSNR value over the traditional MRME technique.

A new coding scheme for image transmission over noisy channel is proposed. Similar to standard image compression, the scheme includes a linear transform followed by successive refinement scalar quantization. Unlike conventional schemes, in the proposed system the quantized transform coefficients are linearly mapped into channel symbols using systematic linear encoders. This fixed-to-fixed length "linear index coding" approach avoids the use of an explicit entropy coding stage (e.g., arithmetic or Huffman coding), which is typically fragile to channel post-decoding residual errors. We use linear codes over GF(4), which are particularly suited for this application, since they are matched to the dead-zone quantizer symbol alphabet and to the QPSK modulation used on the deep-space communication channel. We optimize the proposed system where the linear codes are systematic Raptor codes over GF(4). The rateless property of Raptor encoders allows to achieve a "continuum" of coding rates, in order to accurately match the channel coding rate to the transmission channel capacity and to the quantized source entropy rate for each transform subband and refinement level. Comparisons are provided with respect to the concatenation of state-of-the-art image coding and channel coding schemes used by Jet Propulsion Laboratories (JPL) for the Mars Exploration Rover (MER) Mission., 36 pages, 5 figures, to be submitted to IEEE Trans. on Communications

Deblocking filtering (DF) plays a major role in improving the visual quality for image and video coding. A well-designed DF scheme should achieve a good tradeoff between coding efficiency and coding complexity. The DF algorithm for multiview video coding (MVC) has adopted H.264 DF scheme to improve the video quality, which, however, leads to relatively high coding complexity. In this paper, we propose a low complexity DF algorithm in consideration of view correlation, which exploits the view correlation to skip the boundary strength (BS) computation of macroblocks (MBs) that are coded in motion skip mode. Experimental results show that the proposed algorithm can dramatically reduce DF time (35%-6%) without degrading the visual quality in comparison to the conventional algorithm.

We present a method for analyzing dynamic range along the residual coding and reconstruction pathways during video coding by deriving bounds on the maximum absolute value of intermediary data using a simple combination of triangle inequality and reformulation using Kronecker products. The proposed method is then applied toward analyzing the residual coding and reconstruction process in the emerging High Efficiency Video Coding (HEVC) standard. Our analysis shows that, for an input residual with a bitdepth of (B+1) that uses a uniform quantizer, the dynamic range of quantized levels and dequantized coefficients are no more than (B+7) bits and 17 bits, respectively. Furthermore, a 16 bits transpose buffer is sufficient, while up to 5 bits of bitdepth expansion can occur in the reconstructed residual. The analysis is validated by simulation results with both randomly generated residual and encoding/decoding test video sequences using the HEVC reference software.

In this letter, functional duality between Distributed Source Coding with One Distortion Criterion (DSC-ODC) and correlated messages and Semi-Deterministic Broadcast Channel Coding (SD-BCC) with correlated messages is considered. It is shown that under certain conditions, for a given DSC-ODC problem with correlated messages, a functional dual SD-BCC problem with correlated messages can be obtained, and vice versa. In particular, the correlation structure of the messages in the two dual problems are the same. The source distortion measure and the channel cost measure for this duality are also specified.

The problem of transmitting a pair of correlated Gaussian sources over degraded broadcast channels using optimal separate source and channel codes is studied. Upper bounds are derived for the rate penalty (in terms of channel uses per source symbol) and the power loss endured by separate coding compared to joint coding. Although source-channel separation is suboptimal in general, it is demonstrated that the performance of separate coding comes close to that of optimal joint coding, especially for low distortion pairs. In fact, in some cases, separate coding performs better than the best known joint schemes so far. It is also shown analytically that separate coding is optimal when either of the sources is to be reconstructed in a near-lossless fashion.

Interactive screen sharing requires extremely low latency end-to-end transmission, which in turn requires highly efficient and low-complexity screen compression. In this paper, we present a block-based low-complexity screen compression scheme, in which multiple block modes are adopted to exploit the intra- and inter-frame redundancies. In particular, we classify the intra-coded blocks to pictorial blocks and textual blocks using a proposed fast block classification algorithm, which exploits the discriminative features between the pictorial and the textual blocks. Then, we design a low-complexity, yet efficient, algorithm to compress the textual blocks. We use base colors and escape colors to represent and quantize the textual pixels, which not only achieves high compression ratios but also preserves a high quality on textual pixels. The two-dimensionally predictive index coding and hierarchical pattern coding technologies are used to exploit local spatial correlations and global pattern correlation, respectively. To further utilize the correlation between the luminance and chrominance channels, we propose a joint-channel index coding method. We compare the coding efficiency and the computational complexity of the proposed scheme against the standard image coding schemes such as JPEG, JPEG2000, and PNG, the compound image compressor HJPC, and the popular video coding standard H.264. We also compare the visual quality of the proposed scheme against H.264 intra coding, JPEG2000, and HJPC. The evaluation results show that the proposed scheme achieves superior or comparable compression efficiency with much lower complexity than other schemes in most of the cases.

Distributed video coding (DVC) is a novel video coding paradigm. One approach to DVC is Wyner-Ziv distributed video coding. Quantization step (QS) is one of the most important factors deciding encoder’s coding efficiency. In this paper, an edge classification based Discrete Cosine Transform (DCT) coefficients reorganization method was proposed. The block was first classified into horizontal-edge block, vertical-edge block and other block. Then different scanning order was applied to each class of blocks. In this way, larger coefficients might be grouped together and QS for Alternating Current (AC) coefficients might be reduced. Experimental results show that compared with DISCOVER’s method, the proposed method makes PSNR of reconstructed image increase about 0.5dB at high bit rate.

This paper proposes a hybrid pattern matching/transform-based compression method for scanned documents. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efficiently compressed by a transform-based encoder. The efficiency of this approach is demonstrated using H.264/advanced video coding (AVC) as a high-quality single and multipage document compressor. The proposed method, called advanced document coding (ADC), uses segments of the originally independent scanned pages of a document to create a video sequence, which is then encoded through regular H.264/AVC. The encoding performance is unrivaled. Results show that ADC outperforms AVC-I (H.264/AVC operating in pure intramode) and JPEG2000 by up to 2.7 and 6.2 dB, respectively. Superior subjective quality is also achieved.

A distributed video coding (DVC) system based on wavelet transform and set partition coding (SPC) is presented in this paper. Conventionally the significance map (sig-map) of SPC is not conducive to Slepian-Wolf (SW) coding, because of the difficulty of generating a side information sig-map and the sensitivity to decoding errors. The proposed DVC system utilizes a higher structured significance map, named progressive significance map (prog-sig-map), which structures the significance information into two parts: a high-level summation significance map (sum-sig-map) and a low-level complementary significance map (comp-sig-map). This prog-sig-map alleviates the above difficulties and thus makes part of the prog-sig-map (specifically, the fixed-length-coded comp-sig-map) suitable for SW coding. Simulation results are provided showing the improved rate-distortion performance of the DVC system even with a simple system configuration.

This letter presents a voice activity detection (VAD) approach using non-negative sparse coding to improve the detection performance in low signal-to-noise ratio (SNR) conditions. The basic idea is to use features extracted from a noise-reduced representation of original audio signals. We decompose the magnitude spectrum of an audio signal on a speech dictionary learned from clean speech and a noise dictionary learned from noise samples. Only coefficients corresponding to the speech dictionary are considered and used as the noise-reduced representation of the signal for feature extraction. A conditional random field (CRF) is used to model the correlation between feature sequences and voice activity labels along audio signals. Then, we assign the voice activity labels for a given audio by decoding the CRF. Experimental results demonstrate that our VAD approach has a good performance in low SNR conditions.

The extrema points coding approach is an attractive way to represent the image. This approach will potentially become a new scheme to compress the still image and will make a great progress for mobile visual search technique. According to the idea of extrema points coding, a complete image compression approach is presented in this paper. Based on the Empirical Mode Decomposition (EMD) theory, digital image is decomposed into different sub-bands, where the most important extrema points are extracted. On mid and low frequency sub-bands, a novel compression method with obvious advantages over current methods is brought out. Combined this method with Linderhed's ''coding of the EMD using DCT of variable sampled blocks (VSDCTEMD)'', a complete digital image compression scheme is designed. It improves Linderhed's image compression scheme based on EMD.

This paper proposes efficient techniques to compress a depth video by taking into account coding artifacts, spatial resolution, and dynamic range of the depth data. Due to abrupt signal changes on object boundaries, a depth video compressed by conventional video coding standards often introduces serious coding artifacts over object boundaries, which severely affect the quality of a synthesized view. We suppress the coding artifacts by proposing an efficient postprocessing method based on a weighted mode filtering and utilizing it as an in-loop filter. In addition, the proposed filter is also tailored to efficiently reconstruct the depth video from the reduced spatial resolution and the low dynamic range. The down/upsampling coding approaches for the spatial resolution and the dynamic range are used together with the proposed filter in order to further reduce the bit rate. We verify the proposed techniques by applying them to an efficient compression of multiview-plus-depth data, which has emerged as an efficient data representation for 3-D video. Experimental results show that the proposed techniques significantly reduce the bit rate while achieving a better quality of the synthesized view in terms of both objective and subjective measures.

Intra prediction improves coding performance by reducing inter pixel redundancy. However, to accommodate the use of block transforms, not all pixels can be predicted from reconstructed pixels that are located close to themselves. This causes prediction performance to suffer as pixel values further apart are less correlated. This paper presents additional intra coding modes designed with the goal of improving prediction performance. Experimental results show an average gain of about 2% in the key technical area software when the new modes are incorporated in the current 8×8 prediction modes. Since the new coding modes (8×8) are designed with transform size smaller than coding block size, the modes can also be useful when the source block is larger than the maximum transform size.

In this paper, an efficient iterative algorithm is proposed for the design of multi-channel nearly perfect reconstructed non-uniform filter bank. The method employs the constrained equiripple FIR technique to design the prototype filter for filter banks with novelty of exploiting a new perfect reconstruction condition of the non-uniform filter banks instead of using complex objective functions. In the proposed algorithm, passband edge frequency (@w"p) is optimized using linear optimization technique such that the filter coefficients values at quadrature frequency are approximately equal to 0.707. Several design examples are included to illustrate the efficacy of this methodology for designing non-uniform filter bank (NUFB). It was found that the proposed methodology performs better as compared to earlier reported results in terms of reconstruction error (RE), number of iteration (NOI) and computation time (CPU time). The proposed algorithm is very simple, linear in nature, and easy to implement.

A new video coding algorithm called the first-order-residual/second-order-residual (FOR/SOR) codec is proposed for high definition (HD) video coding in this work. Several advanced coding techniques are adopted in the proposed FOR/SOR codec. For the FOR codec, the well known block-based motion compensated predictive codec is used to exploit temporal and spatial correlations in input image frames. However, it is observed that there still exists structured residual signal after the FOR coding, and a SOR coder is developed to encode residual image frames efficiently. To improve the coding performance furthermore, we consider bit allocation between the FOR and SOR coders at the same block and determine their optimal quantization parameters systematically. It is shown by experimental results that the proposed FOR/SOR codec outperforms H.264/AVC significantly in HD video coding.

This paper presents a voice signal synthesis and coding method in MATLAB. A voice signal is acquisitioned via microphone and saved in a text file. The sound samples from the file are coded with LPC (Linear Predictive Coding), LSF (Line Spectral Frequencies) and DFT (Discrete Fourier Transform) methods. This voice signal synthesis and coding is very important in today's communication via mobile phones. After the all operations the voice signal can be reproduced.