In the framework of block Compressed Sensing (CS), the reconstruction algorithm based on the Smoothed Projected Landweber (SPL) iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA) to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC) to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

Ran Li

Hongbing Liu

Yu Zeng

Yanling Li

Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

The fast development of image encryption requires performance evaluation metrics. Traditional metrics like entropy do not consider the correlation between local pixel and its neighborhood. These metrics cannot estimate encryption based on image pixel coordinate permutation. A novel effectiveness evaluation metric is proposed in this paper to address the issue. The cipher text image is transformed to bit stream. Then, Poker Test is implemented. The proposed metric considers the neighbor correlations of image by neighborhood selection and clip scan. The randomness of the cipher text image is tested by calculating the chi-square test value. Experiment results verify the efficiency of the proposed metrics.

Shanshan Li

Weiyang Sun

Image Encryption Performance Evaluation Based on Poker Test

This study adopts a triangle subdivision scheme to achieve reversible data embedding. The secret message is embedded into the newly added vertices. The topology of added vertex is constructed by connecting it with the vertices of located triangle. For further raising the total embedding capacity, a recursive subdivision mechanism, terminated by a given criterion, is employed. Finally, a principal component analysis can make the stego model against similarity transformation and vertex/triangle reordering attacks. Our proposed algorithm can provide a high and adjustable embedding capacity with reversibility. The experimental results demonstrate the feasibility of our proposed algorithm.

Yuan-Yu Tsai

A Distortion-Free Data Hiding Scheme for Triangular Meshes Based on Recursive Subdivision

Halftone images are commonly printed on books, newspapers, and magazines. How to protect the copyright of these printed halftone images becomes an important issue. Digital watermarking provides a solution for copyright protection. In this paper, we will propose a novel printable watermarking method for dithering halftone images. Based on downsampling and the property of a dispersed dithering screen, the method can resist cropping, tampering, and print-and-scan process attacks. In addition, comparing to Guo et al.&#x2019;s method, the experimental results show that the proposed method provides higher robustness for the above-mentioned attacks and better visual quality in the high-frequency regions of halftone images.

Hui-Lung Lee

Ling-Hwei Chen

A Novel Printable Watermarking Method in Dithering Halftone Images

This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

Zhigao Zeng

Zhiqiang Wen

Shengqiu Yi

Sanyou Zeng

Yanhui Zhu

Qiang Liu

Qi Tong

Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

Cost effective, smooth multimedia streaming to the remote customer through the distributed &#x201c;video on demand&#x201d; architecture is the most challenging research issue over the decade. The hierarchical system design is used for distributed network to satisfy more requesting users. The distributed hierarchical network system contains all the local and remote storage multimedia servers. The hierarchical network system is used to provide continuous availability of the data stream to the requesting customer. In this work, we propose a novel data stream that handles the methodology for reducing the connection failure and smooth multimedia stream delivery to the remote customer. The proposed session based single-user bandwidth requirement model presents the bandwidth requirement for any interactive session like pause, move slowly, rewind, skip some of the frame, and move fast with some constant number of frames. The proposed session based optimum storage finding algorithm reduces the search hop count towards the remote storage-data server. The modeling and simulation result shows the better impact over the distributed system architecture. This work presents the novel bandwidth requirement model at the interactive session and gives the trade-off in communication and storage costs for different system resource configurations.

Soumen Kanrar

Niranjan Kumar Mandal

Video Traffic Flow Analysis in Distributed System during Interactive Session

To improve rate-distortion (R-D) performance, high efficiency video coding (HEVC) increases the intraprediction modes with heavy computational load, and thus the intracoding optimization is highly demanded for real-time applications. According to the conditional probabilities of most probable modes and the correlation of potential candidate subsets, this paper proposes a fast HEVC intramode decision scheme based on the hybrid cost ranking which includes both Hadamard cost and rate-distortion cost. The proposed scheme utilizes the coded results of the modified rough mode decision and the neighboring prediction units so as to obtain a potential candidate subset and then conditionally selects the optimal mode through early likelihood decision and hybrid cost ranking. By the experiment-driven methodology, the proposed scheme implements the early termination if the best mode from the candidate subset is equal to one or two neighboring intramodes. The experimental results demonstrate that the proposed scheme averagely provides about 23.7&#x25; encoding speedup with just 0.82&#x25; BD-rate loss in comparison with default fast intramode decision in HM16.0. Compared to other fast intramode decision schemes, the proposed scheme also significantly reduces intracoding time while maintaining similar R-D performance for the all-intraconfiguration in HM16.0 Main profile.

Hao Liu

Yuexin Jie

Fast HEVC Intramode Decision Based on Hybrid Cost Ranking

Pure Peer to Peer (P2P) network requires enhancing transportation of chunk video objects to the proxy server in the mesh network. The rapid growth of video on demand user brings congestion at the proxy server and on the overall network. The situation needs efficient content delivery procedure, to the video on demand viewer from the distributed storage. In general scenario, if the proxy server does not possess the required video stream or the chunk of that said video, then the same can be smoothly and rapidly streamed to the viewer. This paper has shown that multitier mesh shaped hybrid architecture composed of P2P and mesh architecture increase the number of requests served by the dynamic environment in comparison with the static environment. Optimized storage finding path search reduces the unnecessary query forward and hence increases the size of content delivery to the desired location.

Enhancement of Video Streaming in Distributed Hybrid Architecture

The measurement and evaluation of the QoE (Quality of Experience) have become one of the main focuses in the telecommunications to provide services with the expected quality for their users. However, factors like the network parameters and codification can affect the quality of video, limiting the correlation between the objective and subjective metrics. The above increases the complexity to evaluate the real quality of video perceived by users. In this paper, a model based on artificial neural networks such as BPNNs (Backpropagation Neural Networks) and the RNNs (Random Neural Networks) is applied to evaluate the subjective quality metrics MOS (Mean Opinion Score) and the PSNR (Peak Signal Noise Ratio), SSIM (Structural Similarity Index Metric), VQM (Video Quality Metric), and QIBF (Quality Index Based Frame). The proposed model allows establishing the QoS (Quality of Service) based in the strategy Diffserv. The metrics were analyzed through Pearson&#x2019;s and Spearman&#x2019;s correlation coefficients, RMSE (Root Mean Square Error), and outliers rate. Correlation values greater than 90&#x25; were obtained for all the evaluated metrics.

Diego Jos&#xe9; Luis Botia Valderrama

Natalia Gaviria G&#xf3;mez

Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment

The Harmonic Walk is an interactive physical environment designed for learning and practicing the accompaniment of a tonal melody. Employing a highly innovative multimedia system, the application offers to the user the possibility of getting in touch with some fundamental tonal music features in a very simple and readily available way. Notwithstanding tonal music is very common in our lives, unskilled people as well as music students and even professionals are scarcely conscious of what these features actually are. The Harmonic Walk, through the body movement in space, can provide all these users a live experience of tonal melody structure, chords progressions, melody accompaniment, and improvisation. Enactive knowledge and embodied cognition allow the user to build an inner map of these musical features, which can be acted by moving on the active surface with a simple step. Thorough assessment tests with musicians and nonmusicians high school students could prove the high communicative power and efficiency of the Harmonic Walk application both in improving musical knowledge and in accomplishing complex musical tasks.

Marcella Mandanici

Antonio Rod&#xe0;

Sergio Canazza

The Harmonic Walk: An Interactive Physical Environment to Learn Tonal Melody Accompaniment

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Advances in Multimedia publishes research on the technologies associated with multimedia systems, including computer-media integration for digital information processing, storage, transmission, and representation.

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Advances in Multimedia - Table of contents 2016

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Advances in Multimedia publishes research on the technologies associated with multimedia systems, including computer-media integration for digital information processing, storage, transmission, and representation.

Advances in Multimedia