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In the field of medical applications, typically obtained medical images like X-ray, CT, MRI etc. consists of noise that reduces the visual quality of an image. Therefore, de-noising is essential during the image acquisition process. Though several methods are available for de-noising the image, the performance metrics of wavelets and threshold values to be used are not optimized for assessing the quality of an image. In this paper, DWT techniques with suitable threshold value and five objective quality metrics are used for de-noising the abnormal MRI brain speckle noise image. Quality metrics like Squared Error Mean (SEM), Peak Signal to Noise Ratio (PSNR), Structural content (SC), Structural Similarity Index Method (SSIM), and Absolute Mean Error (AME) are estimated for de-noised MRI brain image are discussed. The quality of the image is assessed depending on the metrics and wavelet threshold techniques. [ABSTRACT FROM AUTHOR]

Malignant and benign types of tumor infiltrated in human brain are diagnosed with the help of an MRI scanner. With the slice images obtained using an MRI scanner, certain image processing techniques are utilized to have a clear anatomy of brain tissues. One such image processing technique is hybrid self-organizing map (SOM) with fuzzy K means (FKM) algorithm, which offers successful identification of tumor and good segmentation of tissue regions present inside the tissues of brain. The proposed algorithm is efficient in terms of Jaccard Index, Dice Overlap Index (DOI), sensitivity, specificity, peak signal to noise ratio (PSNR), mean square error (MSE), computational time and memory requirement. The algorithm proposed through this paper has better data handling capacities and it also performs efficient processing upon the input magnetic resonance (MR) brain images. Automatic detection of tumor region in MR (magnetic resonance) brain images has a high impact in helping the radio surgeons assess the size of the tumor present inside the tissues of brain and it also supports in identifying the exact topographical location of tumor region. The proposed hybrid SOM-FKM algorithm assists the radio surgeon by providing an automated tissue segmentation and tumor identification, thus enhancing radio therapeutic procedures. The efficiency of the proposed technique is verified using the clinical images obtained from four patients, along with the images taken from Harvard Brain Repository. [ABSTRACT FROM AUTHOR]

In this paper, we have combined watermarking and biometrics for possible improvement in owner identification/verification technology. We have proposed and compared wavelet based four blind invisible watermarking methods that have used face image as watermark. Two watermarking methods are based on the discrete wavelet transform (DWT) and rest two watermarking methods are based on the redundant discrete wavelet transform (RDWT). One watermarking method in each transform incorporates weighted binary coding to achieve improved reliability of extracted watermark. Other watermarking methods replace original image coefficients with face image coefficients. We have observed that DWT based watermarking methods outperform RDWT based watermarking methods. We have compared the robustness of the proposed watermarking methods against various common image processing attacks/operations. We have observed that DWT based watermarking method coupled with weighted binary coding has the best performance without attacks; peak signal to noise ratio value of watermarked image is greater than 50 dB and normalized correlation coefficient value of extracted watermark is 1 at the watermark embedding strength of 1. Moreover, the same watermarking method has the best robustness against most of the attacks. [ABSTRACT FROM AUTHOR]

In Scalable Video Coding (SVC), motion estimation and inter-layer prediction play an important role in elimination of temporal and spatial redundancies between consecutive layers. This paper evaluates the performance of widely accepted block matching algorithms used in various video compression standards, with emphasis on the performance of the algorithms for a didactic scalable video codec. Many different implementations of Fast Motion Estimation Algorithms have been proposed to reduce motion estimation complexity. The block matching algorithms have been analyzed with emphasis on Peak Signal to Noise Ratio (PSNR) and computations using MATLAB. In addition to the above comparisons, a survey has been done on Spiral Search Motion Estimation Algorithms for Video Coding. A New Modified Spiral Search (NMSS) motion estimation algorithm has been proposed with lower computational complexity. The proposed algorithm achieves 72% reduction in computation with a minimal (<1dB) reduction in PSNR. A brief introduction to the entire flow of video compression H.264/SVC is also presented in this paper. [ABSTRACT FROM AUTHOR]

Image denoising is an important pre-processing task before further processing of image like segmentation, feature xtraction, texture analysis etc. The purpose of denoising is to remove the noise while retaining the edges and other detailed features as much as possible. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. As a result, there is degradation in visual quality of an image. In this study two sets of experiments are conducted. The objective of first set of study is to compare the performance of the frequency domain filters for noise reduction of the facial and distant images. The objective of the second set of study of is to compare the performance of the frequency domain filters for the different values of the n (order of the filter) and threshold. [ABSTRACT FROM AUTHOR]

Abstract: Many high performance steganographic schemes work at a limited or sparsely distributed set of embedding rates. We have shown that some steganographic changes will be wasted as these schemes are utilized individually for messages of various lengths. To measure the wasted changes and compare different schemes in this respect, we have built a framework based on two new criteria: the Relative Change Waste (RCW) and the Expected Changes per Pixel (ECP). To decrease the wasted changes a systematic combination of schemes is introduced and proved to be equivalent to nonlinear interpolation of points in a two-dimensional space. We have proved that a special case which leads to a linear interpolation – named Scheme Interpolation – is the most efficient combination. The Convex Hull Point Selection and the Waste Aware Interpolation algorithms are then proposed to construct optimally efficient scheme interpolations for any given level of RCW. Examples of the combined schemes are simulated and proved to outperform the well-known schemes presented so far in terms of ECP, RCW, PSNR and efficiency. Practical usage of scheme interpolation, the performance of the more general cases – called multi-scheme interpolation – and achieving the lower bounds of ECP and RCW are fully discussed. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-pixel structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facial dataset. Unlike many existing face-hallucination methods such as the from local-pixel structure to global image super-resolution method (LPS-GIS) and the super-resolution through neighbor embedding, where the prior models are learned by employing the least-square methods, our framework aims to shape the prior model using sparse representation. Then this learned prior model is employed to guide the reconstruction process. Experiments show that our framework is very flexible, and achieves a competitive or even superior performance in terms of both reconstruction error and visual quality. Our method still exhibits an impressive ability to generate plausible HR facial images based on their sparse local structures. [Copyright &y& Elsevier]

Differential Pulse Code Modulation (DPCM) is one of the predictive coding techniques. The number of previous pixels employed in the estimate operation is referred to as the order of the predictor. Predictor using one pixel for estimation is called “first order predictor”. A “second order predictor” utilizes two pixels and an “nth order predictor” would employ n previous pixels. From the results computed in this work, by testing the prediction mean square error (MSE) using different numbers of previous picture elements. The results show that the MSE decreases significantly by using up to three pixels, and further decreases of MSE are rather small by using more than three pixels that means the performance improvement becomes negligible and only a marginal gain beyond a third-order predictor can be achieved. That means, Peak Signal to Noise Ratio (PSNR) increases significantly by increasing the predictor order, the performance improvement becomes negligible beyond third order predictor.

Abstract: In this work, we present a mixed software/hardware implementation of 2-D signals encoder/decoder using dyadic discrete wavelet transform (DWT) based on quadrature mirror filters (QMF); using fast wavelet Mallat's algorithm. This work is designed and compiled on the embedded development kit EDK6.3i, and the synthesis software, ISE6.3i, which is available with Xilinx Virtex-IIV2MB1000 FPGA. Huffman coding scheme is used to encode the wavelet coefficients so that they can be transmitted progressively through an Ethernet TCP/IP based connection. The possible reconfiguration can be exploited to attain higher performance. The design will be integrated with the neutron radiography system that is used with the Es-Salem research reactor. [Copyright &y& Elsevier]

Highlights: [•] Perceptual image assessment is proposed for coder performance evaluation. [•] Proposed assessment uses a linear combination of perceptual measures just based on features. [•] Region-of-Interest coder perceptual evaluation aims at identifying coder behavior. [•] Some perceptual assessments are adequate to evaluate test coders. [ABSTRACT FROM AUTHOR]

Highlights: [•] MRI denoising based on nonlocal neutrosophic set Wiener filtering. [•] Experimenting this method with simulated and clinical MR images. [•] Performance evaluated based on peak signal to noise ratio and structural similarity index. [•] Visual and diagnostic quality of the denoised image well preserved. [ABSTRACT FROM AUTHOR]

Proposed a block-based compressive video sensing algorithm, which allows to pursue video acquisition and video compressed coding synchronously. To explore the temporal redundancy of the video, different sensing strategies were used between reference frames and non-reference frames: for reference frames, the frames were divided to little patches and employed regular compressive sensing to every patch; while for the rest ones, first the frams were divided into blocks in the same size and then compared the blocks with the corresponding block in reference frame, pursue different sensing method according to the results. The frame quality is better because non-reference frame observation could feedback the reference frames. Meanwhile, the sampling rate changes adaptively according to the texture complication. The experimental results with 20% less samples than other methods indicate that the algorithm is more suitable to human eyes and also gets higher PSNR. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposed a hash based steganographic approach in thermal images for authentication. Thermal images used in security measures for surveillance suffer from lack of authenticity. Thermal images are taken as cover images and bits from authenticating images/messages are inserted using a hash function. One, two and three bits per bytes are inserted into the cover images. The hash function increases the robustness of the technique and the adjustment optimized the image fidelity. Various parametric tests are performed and compared with existing techniques which shows better parametric values based on embedding capacity and image fidelity. [Copyright &y& Elsevier]

Abstract: In this paper a G-Let based authentication technique has been proposed to authenticate digital documents through Hough transform generated signature generated from original autograph. The cover image is transformed into G-Let domain to generate n number of G-Lets out of which (n/2)-1 numbers of G-Lets are embedded with secret Hough signature bits for the purpose of authentication or copyright protection. The special feature of AHSG is to optimize the distortion rate, by adjustment at the last stage of the technique, using back propagation. Experimental results are computed and compared with the existing authentication techniques like Li's method, SCDFT, Region-Based method based on Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Image Fidelity (IF), Universal Quality Image (UQI) and Structural Similarity Index Measurement (SSIM) which shows better performance in AHSG, in terms of low computational complexity and better fidelity. [Copyright &y& Elsevier]

Abstract: In this paper a Genetic Algorithm based steganographic technique in frequency domain using discrete cosine transform has been proposed. A 2×2 sub mask of the source image is taken in row major order and Discrete Cosine Transformation is applied on it to generate four frequency components. Two bits of the authenticating image are embedded into each transformed coefficients except the first one. In each coefficient second and third positions from LSB are chosen for embedding in the transform domain. Stego sub intermediate image is generated through reverse transform. Sub mask from this intermediate image is taken as initial population. New Generation followed by Crossover is applied on initial population to enhance a layer of security. New Generation is applied to initial population. Rightmost three bits of each byte are taken, a consecutive bitwise XOR is applied on it in three steps which generates a triangular form. The first bit of each intermediate step is taken as the output and Crossover is performed on two consecutive pixels where two LSB bits of two consecutive bytes are swapped. The dimension of the hidden image is embedded followed by the content. Reverse process is followed during decoding. The proposed scheme obtains high image fidelity, PSNR and high capacity of embedding in stego images compared Chang Chin et al. [1]. [Copyright &y& Elsevier]

In this paper a Daubechies based steganography in frequency domain termed as ATFDD has been proposed where the cover image is transformed into the time domain signal through Daubechies forward transformation, resulting four sub-image components as, "Low resolution", "Horizontal orientation", "Vertical orientation" and "Diagonal orientation". Secret message/image bits stream in varying positions are embedded in 3rd coefficient of every sub image, along with delicate adjustment followed by reverse transformation to generate embedded/encrypted image. The decoding is done through the reverse procedure. The experimental results against statistical and visual attack has been computed and compared with the existing technique like Yuancheng Li's method, Region-Based method and SCDFT in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Image Fidelity (IF) analysis, which shows better performances in ATFDD. [ABSTRACT FROM AUTHOR]

The major growth of information technology is based on the growth of computer networks. The computer network diminished the entire global in a nutshell, via the internet and the intranet capabilities. In the recent year, communicating information within authenticated groups in the text, image and video formats are highly unavoidable one. And in the same manner, there are more possibility that the communicated information to be hacked by the anonymous hacker. The hacker may be passive or active; it is highly risk for many engineering applications like military network. Hence, digital watermarking is merged to rectify the above pitfalls. Watermarking techniques developed for images are mainly classified into visible and invisible approaches. The study further analyses the modern digital watermarking system. Key words: Providing additional information, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Discrete Fourier Transform (DFT), Peak Signal to Noise Ratio (PSNR), sliding square window containing [ABSTRACT FROM AUTHOR]

Abstract: In this paper two separate models of watermarking has been proposed based on wavelet and Z domain along with comparative study in terms of PSNR, MSE and IF. The cover image is passed through transformation based on 2 x 2 mask as sliding window manner in row major order to convert the spatial components of cover image into frequency coefficients. Four bits of authenticating image pixels are embedded into transform coefficients of each mask as watermark of the scheme to achieve the payload of one bpB (bit per Byte). Extraction is made in reverse manner. Results are computed and compared between two steganographic models in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Image Fidelity (IF) which show better performances in Z-domain with enhanced fidelity. [Copyright &y& Elsevier]

Image denoising is a key issue in all image processing researches. The great challenge of image denoising is how to preserve the edges and all fine details of an image when reducing the noise. In this paper, a comparative study of image denoising techniques for underwater SONAR (Sound Navigation and Ranging) images relying on spatial filters is presented. In particular four types of spatial filters (Average, Gaussian, Laplacian of Gaussian and Median filters) are applied to judge the efficiency. On each image, different window size configurations starting from 3x3 to 29x29 are applied and the performances of image filtering techniques are analyzed by the estimation of parametric values such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and execution time for filtering the images. It is observed that by increasing the window size the execution time will increase and PSNR values will decrease. With this analysis and from the results it is found that the optimum filter is Gaussian and the optimum window size is 3×3 for the underwater SONAR images which gives the best execution time, MSE and the PSNR value (37.87dB). [ABSTRACT FROM AUTHOR]

This paper proposes a new variant of parallel particle swarm optimisation (PPSO) known as small population-based modified PPSO (SPMPPSO) for fast motion estimation. The proposed technique is used to reduce computational time for block motion estimation in video. In the said technique, the velocity and position equations of PPSO are modified to achieve adaptive step size for getting true motion vector. The new position of swarm depends on previous motion vector, time decreasing inertia weight and on time-varying acceleration coefficient. The best matching block is predicted by step size/position equation of SPMPPSO. The Von Neumann topology is used as search pattern in the SPMPPSO. In SPMPPSO, small population, i.e. five swarms with which two-step search are used to find best matching block. Zero motion prejudgement is used leads to faster convergence for getting the motion vector. The results of SPMPPSO are compared with those of PPSO and with those of other motion estimation algorithms. The limitations such as computational time, search parameter, initial search and search space are overcome in SPMPPSO. The proposed technique saves computational time up to 94% when compared with other published methods. [ABSTRACT FROM PUBLISHER]

Video compression plays major role in multimedia industry in general. The rapid advances in the video compression algorithms aims at reducing redundancy without compromising the quality. A video captured was encoded using the encoder with each frame processed by dividing it into several motion-blocks. In the encoder part, several motion estimation algorithms were applied. The quality metric, Peak Signal to Noise Ratio (PSNR) for multiple frames was calculated for all available algorithms. From all these it is found that Adaptive Rood Pattern Search (ARPS) algorithm eliminates redundancy without compromising the image quality. This algorithm was used to generate the motion vectors to produce the compensated image, and this image was transformed using Discrete Cosine Transform (DCT) then quantized and encoded in the encoder. For achieving better PSNR and to reduce the number of search points required to generate the motion vector ARPS algorithm is proved superior when compared to the other available searching algorithms. [ABSTRACT FROM AUTHOR]

In this paper a wavelet based steganographic technique TISAWFD has been proposed to automatically identify or authenticate prosecute to prevent or investigate crime. Secrete cameras or CCTV is used to take inputs from active mob, then iris of every visible eye are located and captured from where only IRIS are fetched and enhanced through scaling. IRIS are then transformed into signature through Hough transform and hide itself inside the documents/images in any of the three frequency components generated by wavelet transform using a secret key and a hash function. Experimental results are computed and compared with the existing steganographic techniques like PMEDF (Guo, 2011) and JIN's method (Jin, 2008) in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Standard Deviation (SD) and Image Fidelity (IF) which show better performances in TISAWFD. [ABSTRACT FROM AUTHOR]

Abstract: Image compression is one of the important fields that has useful applications in data storage and transmission. In this research a new algorithm is developed and tested for multiple-image compression and enhancement. The algorithm, in addition, is applied to multiple noisy images. Also, the effect of compression ratio on the peak signal to noise ratio (PSNR) is explored by applying different compression ratios. The developed algorithm gives good compression and noise immunity. It can be used for storage/transmission of encrypted and compressed information. [ABSTRACT FROM AUTHOR]

Due to the engineering demand of oil and gas pipeline crack inspection, a new ultrasonic method based on non-contact ultrasonic transducer known as EMAT has emerged. Because of the large amount of original waveform data and limited speed and capacity of storing device, research on online data compression is needed. A subsection adaptive compression algorithm based on the features of the inspection data is proposed. The compression precision can be adjusted by altering compression threshold. Compression experiments of 250 kHz EMAT guided wave data are conducted using this algorithm. The results indicate that the algorithm has good quality, and can achieve rather high compression ratio at the same time. A compression ratio around 20:1 can be achieved on sample data. Compression quality evaluation is performed using error sequence and PSNR. [ABSTRACT FROM AUTHOR]

In this paper, we present the intelligent multimedia data hiding techniques and their possible applications. An introduction on intelligent multimedia data hiding is described which covers backgrounds, recent advances, methodologies, and implementations. The recently developed research branch called reversible data hiding is also depicted. Two major classes for the implementation of reversible data hiding, namely, the difference expansion method, and the histogram-based scheme, are discussed. With its ease of implementation, the histogram-based reversible data hiding technique is then illustrated with simulation results and actual implementations. Possible extension for our work is also depicted in the concluding remarks. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes new concepts of the all phase biorthogonal transform (APBT) and the dual biorthogonal basis vectors. In the light of all phase digital filtering theory, three kinds of all phase biorthogonal transforms based on the Walsh transform (WT), the discrete cosine transform (DCT) and the inverse discrete cosine transform (IDCT) are proposed. The matrices of APBT based on WT, DCT and IDCT are deduced, which can be used in image compression instead of the conventional DCT. Compared with DCT-based JPEG (DCT-JPEG) image compression algorithm at the same bit rates, the PSNR and visual quality of the reconstructed images using these transforms are approximate to DCT, outgoing DCT-JPEG at low bit rates especially. But the advantage is that the quantization table is simplified and the transform coefficients can be quantized uniformly. Therefore, the computing time becomes shorter and the hardware implementation easier. [Copyright &y& Elsevier]

• Applied six de-noising filters (i.e., Mean, Median, Kuan, Lee, Frost and adaptive Homomorphic) on original and noisy images. These filters are commonly used for speckle noise reduction to demonstrate the filter efficiency across a range of speckle-noise degradation variances. • Results were analyzed based on four image quality metrics (i.e., peak signal to noise ratio (PSNR), root mean square error (RMSE), speckle suppression index (SSI), and standard deviation to mean ratio (STM)). • The metrics were further analyzed by using the statistical tests (i.e., one-way analysis of variance (ANOVA) and Tukey's post hoc test). In the modern-days diagnostics, ultrasound is considered a significant non-invasive imaging technique. However, ultrasound images are frequently contaminated by multiplicative speckle noise. Speckle noise is produced by constructive and destructive interference between ultrasound waves when the object being measured is smaller than the wavelength of the beam. The removal of speckle noise in ultrasound images is possible by using various filters. The current experimental study is aimed at finding the most suitable de-speckling filters for enhancing ultrasound images. The present study involves 102-abdomen ultrasound images degraded by speckle noise and the analysis of eight de-speckling filters (i.e., Mean, Median, Kuan, Lee, Frost, Adaptive Homomorphic, Wiener and Anisotropic Diffusion) is developed to find the optimum de-speckling filter. The results of the given filters are analyzed using the five quality metrics (i.e., PSNR, RMSE, SSI, STM, and SSIM). The metrics are further investigated by using the statistical tests (i.e., one-way ANOVA and Tukey's post hoc test) to support the experimental evaluation. Simulation results showed that the Frost and adaptive Homomorphic filters work well for the ultrasound images degraded with higher value of speckle noise. From the proposed research, it is easy to select the optimal filter, which helps doctors to get fine details of the image. [ABSTRACT FROM AUTHOR]

Because of the iterative process in the rate control algorithm of H.264 draft, it is not suitable for real-time transmission. A two-layer real-time rate control algorithm based on Lagrange optimum algorithm is proposed. This algorithm consists of two layers, namely, the group of pictures (GOP) layer and the frame layer. The simulation results show that the proposed algorithm is competitive in terms of peak signal to noise ratio (PSNR), real bitrates and the Q-value among frames over the original algorithm. [ABSTRACT FROM AUTHOR]

Wireless Local Area Networks (WLANs) such as IEEE 802.11a/g and Hiperlan/2 utilise numerous transmission modes, each providing different throughputs and reliability levels. Many link adaptation algorithms proposed in the literature either maximise the error-free data throughput based on channel conditions or are based on the number of failed transmissions. However, these algorithms do not take into account the content of the data stream and strongly rely on the use of Automatic Repeat Requests (ARQs). Low latency video applications such as real-time video transmission may require no retransmission, or only a limited number of retransmissions. Moreover, completely error-free communication is not essential, especially if robust video compression techniques are applied. In such scenarios, improved decoded video quality can be obtained with a video stream transmitted at a higher bit rate using a higher link speed but with some degree of transmission error, rather than an error-free video stream at a lower bit rate using a lower link speed. In this work, we investigate a link adaptation scheme that improves the Quality of Service (QoS) for video transmission, based on the overall received video quality (Peak Signal to Noise Ratio, PSNR), rather than by maximising the error-free throughput. We also study a practical link adaptation approach that uses PER thresholds at the PHY layer. An empirical study showed that thresholds for switching from one mode to another are much lower (almost error free) than those currently used by throughput based schemes. We show that traditional link adaptation strategies are not appropriate for real-time video transmission with no retransmission. Simulation results using the H.264 video compression standard over IEEE 802.11a are presented. [ABSTRACT FROM AUTHOR]

An efficient image transmission scheme is proposed based on byte partition and adaptive sub-channel distribution technique in Filtered MultiTone (FMT) system over frequency selective slow fading channel. According to the simulation results and analysis of a typical image with matlab, improvement in Peak Signal to Noise Ratio (PSNR) of the received image and low complexity for equalization is demonstrated remarkably. Comparing with no adaptive and no actual channel equalization scheme, the proposed scheme saves over 6 dB when PSNR=40 dB. [ABSTRACT FROM AUTHOR]