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The spatial-domain intra prediction scheme of H.264 has high computational complexity, especially for the High Profile as it incorporates the additional intra 8\,\times\,8 prediction mode. To address this issue, we explore the hierarchy of H.264 mode decision process in this paper and adopt an approach that is in synchrony with the mode decision hierarchy. In particular, we propose a variance-based algorithm for block size decision, an improved filter-based algorithm for prediction mode decision using contextual information, and a selection algorithm for intra block decision that exploits the relation between the rate-distortion characteristic and the best coding type. Performance comparison is provided to show the improvement of the proposed algorithms over previous methods. [ABSTRACT FROM PUBLISHER]

The H.264/AVC achieves higher coding performance than the previous video coding standards, such as MPEG-2 and MPEG-4. In order to achieve this improved coding performance, H.264 adopts various advanced techniques including multiple reference frame motion estimation (MRF-ME), which requires very heavy encoding complexity in proportion to the number of reference frames. In this letter, we propose an efficient priority-based reference frame selection (PRFS) method to reduce the computational complexity. The PRFS method computes the priorities of all reference frames using spatial and temporal correlation of the reference frame index and motion vectors, and selects candidate reference frames to reduce the number of reference frames for each ME block. Experimental results show that the proposed method reduces the computational complexity of the MRF-ME and achieves similar coding performance to that of previous methods. [ABSTRACT FROM PUBLISHER]

A new object-based coding system for a class of dynamic image-based representations called plenoptic videos (PVs) is proposed. PVs are simplified dynamic light fields, where the videos are taken at regularly spaced locations along line segments instead of a 2-D plane. In the proposed object-based approach, objects at different depth values are segmented to improve the rendering quality. By encoding PVs at the object level, desirable functionalities such as scalability of contents, error resilience, and interactivity with an individual image-based rendering (IBR) object can be achieved. Besides supporting the coding of texture and binary shape maps for IBR objects with arbitrary shapes, the proposed system also supports the coding of grayscale alpha maps as well as depth maps (geometry information) to respectively facilitate the matting and rendering of the IBR objects. Both temporal and spatial redundancies among the streams in the PV are exploited to improve the coding performance, while avoiding excessive complexity in selective decoding of PVs to support fast rendering speed. Advanced spatial/temporal prediction methods such as global disparity-compensated prediction, as well as direct prediction and its extensions are developed. The bit allocation and rate control scheme employing a new convex optimization-based approach are also introduced. Experimental results show that considerable improvements in coding performance are obtained for both synthetic and real scenes, while supporting the stated object-based functionalities. [ABSTRACT FROM AUTHOR]

The newest video coding standard called scalable video coding (SVC) provides broad applications in multimedia communications. SVC encoder consumes great computational complexity when compared to previous video coding standards. This paper presents a fast mode decision algorithm that speeds up the SVC encoding process through probabilistic analysis. The mode of the enhancement layer is first predicted by statistical analysis. Afterward, Bayesian theorem is utilized to detect whether the prediction mode of the current macroblock is the best or not. The mode is further predicted and refined by the Markov process. Experimental results show that the proposed algorithm significantly reduces computational complexity with negligible peak signal-to-noise ratio degradation and bitrate increase in the enhancement layers. [ABSTRACT FROM AUTHOR]

A video-based monitoring system must be capable of continuous operation under various weather and illumination conditions. Moreover, background subtraction is a very important part of surveillance applications for successful segmentation of objects from video sequences, and the accuracy, computational complexity, and memory requirements of the initial background extraction are crucial in any background subtraction method. This paper proposes an algorithm to extract initial color backgrounds from surveillance videos using a probability-based background extraction algorithm. With the proposed algorithm, the initial background can be extracted accurately and quickly, while using relatively little memory. The intrusive objects can then be segmented quickly and correctly by a robust object segmentation algorithm. The segmentation algorithm analyzes the threshold values of the background subtraction from the prior frame to obtain good quality while minimizing execution time and maximizing detection accuracy. The color background images can be extracted efficiently and quickly from color image sequences and updated in real time to overcome any variation in illumination conditions. Experimental results for various environmental sequences and a quantitative evaluation are provided to demonstrate the robustness, accuracy, effectiveness, and memory economy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Real-time multiuser multimedia applications, such as surveillance or monitoring using multiple cameras, have recently started to be deployed over flexible and low-cost multihop wireless networks. In such multimedia systems, the various sources (cameras) share the limited network resources and collaboratively forward the captured video streams to a remote central monitor. However, existing resource allocation schemes often ignore the dynamic application-layer video and network characteristics by focusing on the steady-state or worstcase operating conditions. This may result in inefficient allocation of the network resources. In this paper, we focus on determining whether the resource allocation for wireless video surveillance systems should be performed based on steady-state or worstcase operating conditions, or whether perpetual adaptation to the dynamically changing source and network conditions is desirable. We analyze three different types of solutions that have different information requirements: a centralized optimization approach, a decentralized game-theoretic approach (which guarantees a stable allocation), and a distributed greedy approach (which perpetually adapts allocation based on the local information exchanged among the neighboring nodes). We compare these three approaches using the following four metrics: 1) the total video quality; 2) the computational complexity; 3) the required control information overhead; and 4) the timely adaptation to the network and source variation. We show that in a static network, the game theoretic resource allocation is only better than the distributed greedy approach when the network transmission rates are high. In a dynamic network, the distributed greedy approach can outperform the other two approaches significantly in terms of video quality (peak signal-to-noise ratio). This shows that resource allocation solutions for multicamera wireless surveillance networks need to explicitly consider both the dynamic source characteristics and network conditions, rather than always relying on stable, but predetermined, allocations. [ABSTRACT FROM AUTHOR]

Rate control plays an important role in regulating the bit rate to meet the bandwidth and storage requirement. Most existing video encoders regulate the bit rate by adjusting the quantization step size. We propose to incorporate a new dimension: the quantization rounding offset into rate control. In this paper, we present a rate control algorithm with adaptive rounding offsets (ARO) that jointly adjusts the quantization step size and the rounding offset for high bit rate accuracy. Different from the quantization step size that has a limited number of choices, the rounding offset is a continuously adjustable variable that allows the rate control algorithm to reach any precision in principle. Our extensive experimental results show that the proposed ARO algorithm significantly improves the rate control accuracy at almost no extra computational complexity. Compared with the p-domain rate control, the ARO algorithm reduces the rate control errors from about 2% to 0.5% for INTRA frames, and 5% to 1.5% for INTER frames. Our experiments also demonstrate that ARO provides the extra benefit of smoother visual quality. [ABSTRACT FROM AUTHOR]

This letter tackles the problem of reducing the complexity of H.264 decoding. Since deblocking accounts for a significant percentage of H.264 decoding time, our focus is on the H.264 in-loop deblocking filter. Observing that branch operations are costly and that in the deblocking process there are events with significantly high probability of occurrence, we regroup and simplify the branch operations. We apply the idea of Huffman tree optimization to speed up the boundary strength derivation and the true-edge detection by taking advantage of the biased statistical distribution. Our analyses and experiments show that the proposed techniques can reduce the deblocking computation time typically by a factor of more than seven times, while maintaining the bit-exact output. [ABSTRACT FROM AUTHOR]

In this paper, the one-dimensional (1-D) fast 8 x 8 inverse integer transform algorithm for Windows Media Video 9 (WMV-9/VC-1) is proposed. Based on the symmetric property of the integer transform matrix and the matrix operations, which denote the row/column permutations and the matrix decompositions, the efficient fast 1-D 8 x 8 inverse integer transform is developed. Therefore, the computational complexities of the proposed fast inverse transform are smaller than those of the direct method and the previous fast method. With low complexity, the proposed fast algorithm is suitable to accelerate the video coding computations. [ABSTRACT FROM AUTHOR]

The displayed gray level of a plasma display panel (PDP) is often different from the intended target gray level because the displayed level is affected by the load of the panel. The effect of the load on the displayed gray level is decomposed into three factors: total load; line load magnitude; and line load distribution. Previous attempts to reduce this difference (i.e., error) have achieved only limited success because they have not taken three factors into consideration altogether. This paper proposes a new method that compensates for the error caused by all three factors. The proposed method first attempts to compensate for the error caused by line load magnitude and distribution. To this end, the error generated by one sub-field of a PDP is propagated to and compensated for by the remaining sub-fields. The amount of the error is reduced for every incidence of error propagation and, consequently, the final amount of error is reduced to a negligible level. To reduce the computational complexity for the evaluation of the amount of the error caused by the line load distribution, an iterative method is proposed to derive the effect of line load distribution on each cell from its adjacent cell. When sub-field coding is completed for a whole cells on a panel, total load of each sub-field is obtained and the error caused by total load is compensated for by controlling the number of sustain pulses for each sub-field. A significant error reduction is achieved, which shown by simulations and experiments with a 42-in. PDP set, including 91.2% reduction of the mean absolute error obtained through simulations and 69.7% reduction of luminance variation range caused by the load variation in experiments. [ABSTRACT FROM AUTHOR]

This paper presents a bit-depth scalable coding solution that is compatible with the scalable extension of H.264/Advanced Video Coding (AVC), also referred to as scalable video coding (SVC). The proposed solution is capable of providing an 8-bit AVC main profile or high-profile base layer-coded bitstream multiplexed with a higher bit-depth-enhancement layer coded bitstream generated through macroblock level inter-layer bit-depth prediction. New decoding processes for inter-layer prediction are introduced to enable bit-depth scalability. Compatibility with other types of scalability in the SVC standard—temporal, spatial, and SNR scalability—is ensured. It also supports the single-loop decoding required in the SVC specification. Further- more, it supports adaptive inter-layer prediction to determine whether or not the inter-layer bit-depth prediction shall be invoked. This solution is implemented on the basis of the SVC reference software Joint Scalable Video Model version 8.12. Experimental results are presented on 8-bit to 10-bit bit-depth scalability and also combined bit-depth and spatial scalability. [ABSTRACT FROM AUTHOR]

Intra-mode and inter-mode predictions have been made available in H.264/AVC for effectively improving coding efficiency. However, exhaustively checking for all the prediction modes for identifying the best one (commonly referred to as exhaustive mode decision) greatly increases computational complexity. In this paper, a fast mode decision algorithm, called the motion activity-based mode decision (MAMD), is proposed to speed up the encoding process by reducing the number of modes required to be checked in a hierarchical manner, and is as follows. For each macroblock, the proposed MAMD algorithm always starts with checking the rate-distortion (RD) cost computed at the SKIP mode for a possible early termination, once the RD cost value is below a predetermined "low" threshold. On the other hand, if the RD cost exceeds another "high" threshold, then this indicates that only the intra modes are worthwhile to be checked. If the computed RD cost falls between the above-mentioned two thresholds, the remaining seven modes, which are classified into three motion activity classes in our work, will be examined, and only one of the three classes will be chosen for further mode checking. The above-mentioned motion activity can be quantitatively measured, which is equal to the maximum city- block length of the motion vector taken from a set of adjacent macroblocks (i.e., region of support, ROS). This measurement is then used to determine the most possible motion-activity class for the current macroblock. Experimental results have shown that, on average, the proposed MAMD algorithm reduces the computational complexity by 62.96%, while incurring only 0.059 dB loss in PSNR (peak signal-to-noise ratio) and 0.19% increment on the total bit rate compared to that of exhaustive mode decision, which is a default approach set in the JM reference software. [ABSTRACT FROM AUTHOR]

In block matching, the matching criterion plays a pivotal role in both matching accuracy and computational complexity. Mean squared error (MSE) is one most widely accepted benchmark for matching accuracy. To avoid multiplication operations for simpler implementation, the sum of absolute difference (SAD) is normally taken as a substitute to approximate MSE. In this paper, we first examine statistically the quantitative deviation of SAD from MSE in terms of maximum and average deviations. To minimize the average deviation, a new measure, namely, weighted sum of absolute difference (WSAD), is proposed in a two-element case first, for which an optimal weight is obtained theoretically. The weight is approximately adapted to 1/2 so that the weighting operation can be simplified to a shift operation, and the resulting multiplication-free WSAD also shows better matching accuracy with a smaller deviation from MSE than SAD. The two-element WSAD is further extended to a multi-element case in a multilevel pyramid structure. The proposed WSAD is experimentally validated by applying it in block motion estimation for video coding, showing better rate-distortion performance than SAD. [ABSTRACT FROM AUTHOR]

The H.264 video coding standard supports efficient coding of video at the expense of high computational complexity. This work addresses the problem of maintaining acceptable video coding performance in a computation-constrained application scenario. A complexity management approach is proposed for an H.264 encoder running in a processor/power-constrained environment. We hypothesize that, in a power-constrained application such as mobile video telephony, good perceptual quality requires a balance between a high frame rate and acceptable image quality. Therefore, the objective of the complexity management approach is to maintain a smooth video frame rate whilst ensuring that the frame quality is not degraded unacceptably. A frame-level algorithm calculates a target coding time for each frame and drops frames when necessary to maintain acceptable image quality. A per-frame algorithm controls the coding complexity of each frame in order to achieve the target coding time. The performance of the approach is evaluated by carrying out subjective tests and comparing the managed complexity encoder with a reference encoder in a computation-constrained scenario. Subjective results show that the managed complexity encoder consistently achieves superior perceptual video quality ratings compared to the reference encoder. [ABSTRACT FROM AUTHOR]

A complexity reduction algorithm tailored for the H.264/AVC encoder is described. It aims to alleviate the computational burden imposed by Lagrangian rate distortion optimization in the inter-mode selection process. The proposed algorithm is described as a hierarchical structure comprising three levels. Each level targets different types of macroblocks according to the complexity of the search process. Early termination of mode selection is triggered at any of the levels to avoid a full cycle of Lagrangian examination. The algorithm is evaluated using a wide range of test sequences of different classes. The results demonstrate a reduction in encoding time of at least 40%, regardless of the class of sequence. Despite the reduction in computational complexity, picture quality is maintained at all bit rates. [ABSTRACT FROM AUTHOR]

In this letter, we investigate the error resilience properties of JPEG2000. We identify the dependencies among coding passes of a codeblock codestream, and determine the sections of the codestream that can be salvaged in the presence of errors. In our analysis, we consider the effects of mode variations provided by the standard. The proposed methods are derived using the existing dependency structure of coding passes and do not require a substantial increase in computational complexity of the decoder. Experimental results indicate that the proposed methods can improve the error resilience performance substantially. [ABSTRACT FROM AUTHOR]

In this paper, we propose a systematic approach that approximates a target dictionary to reduce the complexity of a matching pursuit encoder. We combine calculation of the inner products and maximum atom extraction of a matching pursuit video coding scheme based on eigendictionary approximation and tree-based vector quantization. The approach makes the codec design and optimization cleaner and more systematic than previous dictionary approximation methods. We vary the quality of approximation to demonstrate the tradeoff between computational complexity and coding efficiency. The experiment results show that our codec achieves speed-up factors of up to 100 with a performance loss of less than 0.1 dB. We use double-stimulus impairment scale scores to evaluate the perceptual quality of our approach for different levels of complexity. [ABSTRACT FROM AUTHOR]

Characterized by their distinctive motion patterns, temporal textures are natural phenomenon exhibiting spatio-temporal regularity with indeterminate spatial and temporal extent. This paper presents a real-time motion-based temporal texture characterization technique for the first time using block-based motion measures with very high classification accuracy against the popular opinion that such an accurate characterization is only possible using pixel-based measures. Finding an optimal weight ratio between space and time domain features where the accuracy of this block-based technique peaks has been the essence of this success. Computational complexity analyses and classification results clearly demonstrate the capability of the proposed technique in producing comprehensive classification results comparable to the best pixel-based technique with overwhelming reduction in computational complexity. [ABSTRACT FROM AUTHOR]

Within the framework of spatiotemporal attention detection, this paper proposes an efficient method for focus of attention (FOA) detection which involves combining adaptively the spatial and motion attention to form an overall attention map. Without computing motion explicitly, it detects motion attention using the rank deficiency of grayscale gradient tensors. We also propose an attention-driven shot matching method using primarily FOA. Experimental results demonstrate the effectiveness of the proposed FOA detection method and the proposed shot matching approach outperforms other published methods. [ABSTRACT FROM AUTHOR]

This work presents a new class of algorithms for super-resolution (SR) of image sequences. This class of algorithms estimates simultaneously all frames of a sequence by employing an iterative minimization of a regularized cost function. Similarly to other SR techniques, the proposed approach exploits the correlation among the frames of the sequence. This correlated information helps to improve the resolution of the captured images. By employing the motion information only in the prior term of the cost function, the proposed method achieves a better fidelity and more robust performance, when compared to other methods. This original approach provides a fidelity equivalent to the obtained by the simultaneous methods, while achieving a lower computational complexity. The isolation of the motion equations in the prior term allows an increased control over the motion errors, and as a consequence, provides an improved robustness. The performance of the proposed method is discussed and compared with other methods in the literature. In the comparative experiments, it is considered both the minimization over the Euclidean norm, which is employed to achieve low computational complexity, and the minimization over the Huber norm or ℓ1 norm, which is used to produce images with sharp edges and higher robustness to large motion errors. [ABSTRACT FROM AUTHOR]

In order to take advantage of the byte-type data parallelism in the existing single-instruction multiple-data (SIMD) technique, this paper introduces the concept of 8-bit partial sums, obtained by a 4-bit right-shift operation on the sum of the 16 luminance values in a column of a 16 × 16 block of a video frame. Since these partial sums are of only eight bits, eight of them can be processed concurrently in a single 64-bit SIMD register. A method of employing these partial sums in order to speed up a given block motion-estimation algorithm is then proposed. The notion of the 8-bit partial sums is extended to the four-level case. It is shown that there are 15 possible methods of utilizing these multilevel 8-bit partial sums to accelerate a block motion-estimation algorithm without any loss of accuracy of the algorithm. Each of these 15 methods is used in the full-search algorithm to determine the one that provides the lowest computational complexity. This method is adopted as the chosen scheme to accelerate various block motion-estimation algorithms. Extensive simulations are carried out on eight video sequences showing that substantial speed-up can be achieved when the chosen scheme is incorporated with the various motion-estimation algorithms. The simulation results also demonstrate that the implementation on SIMD architectures can further accelerate the execution of the proposed scheme by more than 93% percent. [ABSTRACT FROM AUTHOR]

In this paper, we propose a generalized discrete cosine transform (DCT) decimation scheme for DCT-domain spatial downscaling which performs two-fold decimation on subframes of a flexible size larger than the traditional 8 × 8 block size to improve the visual quality. Efficient sparse-matrix representations are then derived to reduce the computation of the proposed DCT decimation method. We compare the antialiasing filtering performances and computational complexities of the proposed downscaling scheme with the existing DCT-domain and pixel-domain downscaling schemes. Our analysis shows that the proposed scheme can reduce the aliasing artifact compared to the pixel-domain downscaling schemes, whereas the computational complexity may be increased. Experimental results are reported to show the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

The coding efficiency of a Wyner-Ziv video codec relies significantly on the quality of side information extracted at the decoder. The construction of efficient side information is difficult thanks in part to the fact that the original video sequence is not available at the decoder. Conventional motion search methods are widely used in the Wyner-Ziv video decoder to extract the side information. This substantially increases the Wyner-Ziv video decoding complexity. In this paper, we propose a new method to construct side estimation based on the idea of universal prediction. This method, referred to as Wyner-Ziv video coding with universal prediction (WZUP), does not perform motion search or assume an underlying model of the original input video sequences at the decoder. Instead, WZUP estimates the side information based on its observations on the past reconstructed video data. We show that WZUP can significantly reduce decoding complexity at the decoder and achieve a fair side estimation performance, thus making it possible to design both the video encoder and the decoder with low computational complexity. [ABSTRACT FROM AUTHOR]

3-D video will be the most prominent video technology in the next generation. Among the 3-D video technologies, stereo video systems are considered to be realized first in the near future. Stereo video systems require double bandwidth and more than twice the computational complexity relative to mono-video systems. Thus, an efficient coding scheme is necessary for transmitting stereo video. In this paper, a new structure of prediction core in stereo video coding systems is proposed from the algorithm level to the hardware architecture level. The joint prediction algorithm (JPA), which combines three prediction schemes, is proposed for high coding efficiency and low computational complexity. It makes the system outperform MPEG-4 temporal scalability and simple profile by 2-3 dB in rate-distortion performance. Besides, JPA also utilizes the characteristics of stereo video and successfully reduces about 80% computational complexity. Then, a new hardware architecture of the prediction core based on JPA and a modified hierarchical search block-matching algorithm is proposed. With a special data flow, no bubble cycles exist during the block-matching process. The proposed architecture also adopts the near-overlapped candidates reuse scheme to save the heavy burden of data access. Besides, both on-chip memory requirement and off-chip memory bandwidth can be reduced by the proposed new scheduling. Compared with the hardware requirement for the implementation of full search block-matching algorithm, only 11.5% on-chip SRAM and 3.3% processing elements are needed with a tiny PSNR drop, making it area-efficient while maintaining high stereo video quality and processing capability. [ABSTRACT FROM AUTHOR]

Although the conventional post-compression rate distortion (PCRD) optimum algorithm in JPEG2000 can provide excellent rate-distortion performance, it remains troublesome for VLSI design. It requires high-complexity computation and a large quantity of working memory. In this paper, a novel rate-control system for JPEG2000 image coding, which consists of three stages, is proposed to efficiently reduce the computational complexity and memory usage, as well as maintaining the high image comparable with PCRD. In the precoding stage, the rate allocation for the image tiles (RAIT) can allocate the bit rates for different image tiles based on their internal information; moreover, in order to make VLSI design easier, the image edge-detect algorithms and the prediction algorithms are used to evaluate the information of the image tiles. In the tier1 coding stage, according to the given bit rate, the rate allocation based on the rest rate distortion (RARRD) can adaptively truncate code stream based on the rest rate distortion of the current image tile and the rate-distortion (RD) slope of the current coding pass during the current code-block coding, and all of the truncated data need not be encoded and stored. In the post-coding stage, a new fast rate control with approximately optimum truncation (RCAOT) can get the approximately optimum truncation points through searching among the 256 quality layers once, which are divided based on the 8-b RD-slopes expressed by means of a logarithm. This system can not only maintain high image quality through RCAOT and RAIT but also save working memory and encoding time by means of RARRD and RCAOT. Experimental results show that, for the image which has distinct objects and background, the PSNR of the reconstructed images compressed by our rate-control system are much higher than those using PCRD; for other images, our system has the comparative effect as PCRD. [ABSTRACT FROM AUTHOR]

A reduced-complexity convolutional formulation is presented for systolic implementation of the discrete cosine transform, where N-point transform can be computed by four numbers of nearly (N/4)-point circular-convolution-like operations. The proposed algorithm not only provides a reduction of computational complexity by four times over the conventional formulation, where N-point transform is computed via (N - 1)-point cyclic convolution, but also leads to concurrent pipelined execution in linear systolic arrays. It is shown that the multiplications in the processing elements can be implemented by lookup-tables using dual-port ROM. Two variants of systolic structures using ROM-based multipliers are presented for efficient implementation of the proposed algorithm. The proposed structures are found to offer significant saving of hardware, require less latency, and yield more throughput over the existing structures. Apart from simplicity and regularity, the proposed structures would also have flexibility of implementation by CORDIC circuits and canonical-signed-digit-based multipliers as well. [ABSTRACT FROM AUTHOR]

H.264/AVC significantly outperforms previous video coding standards with many new coding tools. However, the better performance comes at the price of the extraordinarily huge computational complexity and memory access requirement, which makes it difficult to design a hardwired encoder for real-time applications. In addition, due to the complex, sequential, and highly data-dependent characteristics of the essential algorithms in H.264/AVC, both the pipelining and the parallel processing techniques are constrained to be employed. The hardware utilization and throughput are also decreased because of the block/MB/frame-level reconstruction loops. In this paper, we describe our techniques to design the H.264/AVC video encoder for HDTV applications. On the system design level, in consideration of the characteristics of the key components and the reconstruction loops, the four-stage macroblock pipelined system architecture is first proposed with an efficient scheduling and memory hierarchy. On the module design level, the design considerations of the significant modules are addressed followed by the hardware architectures, including low-bandwidth integer motion estimation, parallel fractional motion estimation, reconfigurable intrapredictor generator, dual-buffer block-pipelined entropy coder, and deblocking filter. With these techniques, the prototype chip of the efficient H.264/AVC encoder is implemented with 922.8 K logic gates and 34.72-KB SRAM at 108-MHz operation frequency. [ABSTRACT FROM AUTHOR]

Matching pursuit (MP) is a greedy algorithm that decomposes a signal into a linear combination of bases within an overcomplete dictionary. The MP algorithm is usually only approximated due to its massive computational complexity. By approximating a residual in a subspace, we propose a multiple blocks MP update algorithm for video coding that achieves a faster and better MP approximation than traditional algorithms. As the subspace is dependent on a residual, our algorithm is content-dependent. We evaluate the coding performance, including the peak signal-to- noise ratio, runtime, and subjective quality, of our algorithm and compare it with traditional MP algorithms. [ABSTRACT FROM AUTHOR]

A complexity reduction algorithm for an H.264 encoder is proposed. Computational savings are achieved by identifying, prior to motion estimation, macroblocks (MBs) that are likely to be skipped and hence saving further computational processing of these MBs. This early prediction is made by estimating a Lagrangian rate-distortion cost function which incorporates an adaptive model for the Lagrange multiplier parameter based on local sequence statistics. Simulation results demonstrate that the algorithm can achieve computational savings of 19%-67% (depending on the source sequence) with no significant loss of rate-distortion performance. [ABSTRACT FROM AUTHOR]

The embedded multireference frames selection with variable block-size motion compensation model drastically in- creases the computational complexity of the H.264/AVC video coding standard. This paper proposes an adaptive hierarchical motion estimation (ME) algorithm for H.264/AVC with the objective of minimizing the complexity while maximizing the visual quality. The proposed algorithm is based on a framework that exploits the "history" of the motion intensity from a video sequence in order to control ME. The complexity and memory requirement for this meta information is low. The algorithm determines the motion intensity of a video sequence at three levels and accordingly employs different ME techniques. The results certify that the history-based hierarchical information can be very effective in improving the efficiency of ME. [ABSTRACT FROM AUTHOR]

The block-based discrete cosine transform (BDCT) is often used in image and video coding. It may introduce block artifacts at low data rates that manifest themselves as an annoying discontinuity between adjacent blocks. In this paper, we address this problem by investigating a transform-domain Markov random field (TD-MRF) model. Based on this model, two block artifact reduction postprocessing methods are presented. The first method, referred to as TD-MRF, provides an efficient progressive transform-domain solution. Our experimental results show that TD-MRF can reduce up to 90% of the computational complexity compared with spatial-domain MRF (SD-MRF) methods while still achieving comparable visual quality improvements. We then discuss a hybrid framework, referred to as TSD-MRF, that exploits the advantages of both TD-MRF and SD-MRF. The experimental results confirm that TSD-MRF can improve visual quality both objectively and subjectively over SD-MRF methods. [ABSTRACT FROM AUTHOR]

We present a framework for the systematic analysis of video encoding complexity, measured in terms of the number of motion estimation (ME) computations, that we illustrate on motion compensated wavelet video coding schemes. We demonstrate the graceful complexity scalability of these schemes through the modification of the spatiotemporal decomposition structure and the ME parameters, and the use of spatiotemporal prediction. We generate a wide range of rate-distortion-complexity (R-D-C) operating points for different sequences, by modifying these options. Using our analytical framework we derive closed form expressions for the number of ME computations for these different coding modes and show that they accurately capture the computational complexity independent of the underlying content characteristics. Our framework for complexity analysis can be combined with rate-distortion modeling to determine the encoding structure and parameters for optimal R-D-C tradeoffs. [ABSTRACT FROM AUTHOR]

The new video coding standard, H.264/MPEG-4 AVC, uses variable block sizes ranging from 4 × 4 to 16 × 16 in interframe coding. This new feature has achieved significant coding gain compared to coding a macroblock (MB) using fixed block size. However, this feature results in extremely high computational complexity when brute force rate distortion optimization (RDO) algorithm is used. This paper proposes a fast intermode decision algorithm to decide the best mode in intercoding. It makes use of the spatial homogeneity and the temporal stationarity characteristics of video objects. Specifically, spatial homogeneity of a MB is decided based on the MB's edge intensity, and temporal stationarity is decided by the difference of the current MB and it colocated counterpart in the reference frame. Based on the homogeneity and stationarity of the video objects, only a small number of intermodes are selected in the RDO process. The experimental results show that the fast intermode decision algorithm is able to reduce on the average 30% encoding time, with a negligible peak signal-to-noise ratio loss of 0.03 dB or, equivalently, a bit rate increment of 0.6%. [ABSTRACT FROM AUTHOR]

Many studies have performed transcoding of com- pressed video streams in the discrete cosine transform (DCT) domain to reduce computational complexity. On the other hand, most video compression standards recommend motion compensation in the spatial domain. Thus, compressed data that is motion-compensated in the spatial domain should be motion-compensated in the transform domain for the transform-domain transcoding. However, this combination of encoding in the spatial domain and decoding in the transform domain degrades image quality due to mismatches of the inverse DCT and motion compensation. There have been few investigations into this mismatch problem. In this paper, we establish that the rounding in calculation is the major cause of the mismatch. We investigate the mismatch problem in detail and propose a precision lifting method to reduce the effects of the mismatch problem. Experimental results show that our proposed method can effectively reduce the mismatch problem. [ABSTRACT FROM AUTHOR]

Zernike moments have been proven to be very powerful image descriptors. However, their computational complexity makes them unsuitable for real-time applications. In this paper, a mathematical relationship between geometric and Zernike moments is extracted. In this way, the computation of geometric moments is adequate to derive Zernike moments. Since geometric moments can be efficiently implemented in hardware and their calculation can be performed in real-time, we propose here a new real-time hardware architecture for the computation of Zernike moments. This method outperforms existing software approaches, especially for large images, allowing real-time processing of images up to 4 Mpixels. [ABSTRACT FROM AUTHOR]

The MPEG-4 core profile enables object-based coding. A core profile encoder may also have to be able to carry out simple profile frame-based coding. Frame-based coding is, for instance, needed when the object-based functionalities are not used or the target decoder has only simple profile capabilities. cellular nonlinear networks (CNN) offer an effective method to implement the segmentation needed in object-based coding. CNN can be implemented very efficiently with dedicated parallel processor arrays. These parallel processor arrays can integrated with sensor arrays in low-power low bit-rate mobile video encoders. it is shown here that an object-based core profile encoder can have advantages in frame-based simple profile encoding. The intermediate results of a CNN segmentation algorithm can be used in computational complexity reduction of motion estimation (ME). The CNN intermediate results indicate areas of motion within a frame. The areas without motion can be then used to stop the ME or to indicate MPEG-4 skip modes. All block-based ME algorithms can benefit from this knowledge. The intermediate results of the segmentation algorithm are evaluated with the full search and MVFAST ME algorithms. Rate-distortion and computational complexity results are computed with four different reference frame schemes. Considerable improvement in output bits and computational complexity is seen without loss in subjective video quality. The method also has applications in scene change detection. [ABSTRACT FROM AUTHOR]

We propose a new highly scalable wavelet transform-based Image coder, called S-SPECK, on the extension of a well-known zero-block image coder SPECK, by achieving not only distortion scalability, resolution scalability, and region of interest (ROI) retrievability, but also excellent compression performance with very low computational complexity. Though new features have been introduced into S-SPECK, our coder is quite competitive with SPECK on compression performance (peak signal-to-noise ratio) and computational complexity (encoding and decoding times) at various bit rates for standard test images. A novel quality layer formatting method is implemented in S-SPECK, which is much simpler and faster than PCRD used in JPEG2000. Extensive experiments have verified all our claims for S-SPECK. [ABSTRACT FROM AUTHOR]

An improved fast full-search algorithm for motion estimation is proposed. The computations process of the sum of absolute difference and the multilevel successive elimination algorithm (MSEA) are theoretically analysed. Based on these analyzes, a new detection criterion and an estimation of the starting level are proposed in order to reduce the computations required for judging invalid candidate blocks. The simulation results show that the proposed algorithm achieves a computational timesaving of about 40% compared with the MSEA. [ABSTRACT FROM AUTHOR]

This paper presents a fast binary motion estimation (BME) algorithm using diamond search pattern for MPEG-4 shape coding, which is the key technology for supporting the content-based video coding. Based on the properties of binary shape information, a boundary mask for efficient search positions can be generated. Therefore, a large number of search points can be skipped. Simulation results show that our algorithm combined with diamond shaped zones takes equal bit rate in the same quality but reduces the number of search points marvelously in BME to 0.6% compared with full search algorithm, which is described in MPEG-4 verification mode. The proposed algorithm will reduce computational complexity of shape coding significantly and be suitable for real-time software and hardware applications of MPEG-4 shape coding. [ABSTRACT FROM AUTHOR]

In this letter, we explore the rate-distortion (R-D) characteristics of binary shape information in the MPEG-4 standard. The shape coding scheme is a block-based context-based arithmetic encoding approach and distortion is introduced by down and up sampling. Generally, the shape bit rate and non- normalized distortion increase in proportion with the number of border blocks. At any given resolution scale, the more complex an object, the more distortion that is introduced. Consequently, we propose an R-D model based on the parameters derived from the border blocks and a block-based shape complexity for the video object. The computational complexity is much lower than other existing methods. Experimental results show that it can accurately predict the bit rate and distortion of the binary shape for rate control purposes. [ABSTRACT FROM AUTHOR]