Distributed video coding thesis

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Benefits from Distributed Video Coding DVC and Compressive sensing CS , we propose a video coding solution which emphasize on improving the quality of side information SI frames in decoder to fulfill the requirements of low-complexity, efficient signal sensing and encoding. The key frames are H.

The resulting measurement vector y is quantized and stored in the buffer. The encoder sends fixed amounts of measurements upon the decoder requests. The decoding process starts by creating the SI for each WZ frame. The statistical motion field estimation is performed using the de-quantized measurements and, hence the SI frame is re-estimated and contributes to a quality increase.

Each block is decoded using a belief propagation BP decoder with the a posteriori probabilities of signals approximated by a Laplacian distribution. The decoder requests more measurements via feedback channel until the decoding task is considered successful. Finally, the key frames and WZ frames together generate the decoded video sequence.

Experimental results indicate that with the aid of the proposed SI generation methods, the signal reconstruction quality can be much improved as compared with the existing CS-based DVC codecs, especially for high-motion videos.

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Distributed Source Coding: Theory, Algorithms and Applications

Overview Project Description People Resource. Distributed Video Coding with Compressive Measurements Academic project, This project presents a novel distributed video coding DVC scheme using compressive sensing CS that achieves low-complexity for encoding and efficient signal sensing. Contributions Employ a block-wise sparse CS encoding matrix to improve the coding efficiency Develop an enhanced SI generation algorithm with statistical motion field estimation in the measurement domain Model the signal by a probability distribution function for further CS decoding Papers Tseng, Hsiao-Yun , Yun-Chung Shen, and Ja-Ling Wu.

ACM, Project Description With the increasing development of wireless networks and the widespread popularity of handheld devices, a vision of video acquisition, processing, and sharing across applications with limited computing power has emerged.


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Volume 10 Issue 1. Issue 2.

Selected topics on distributed video coding

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Distributed video coding

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Choose an option ePUB Mobi. Product price. Product added! Browse Wishlist. The product is already in the wishlist! Preface Chapter 1. Introduction Chapter 2.

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Turbo-Codes for Channel Coding Chapter 3. Applications in Distributed Video Coding Chapter 6. Conclusion References.