Compressed Sensing Video Coding Implementation

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Resource Overview

MATLAB-based compressed sensing video coding program implementing latest DCVS theoretical algorithms. Utilizes BWHT (Walsh-Hadamard Matrix) for sparse representation and GPSR algorithm for reconstruction with optimized signal recovery performance.

Detailed Documentation

This article provides a comprehensive overview of MATLAB-based compressed sensing video coding implementation. We thoroughly examine the latest DCVS theoretical algorithm framework, detailing the implementation of BWHT (Walsh-Hadamard Matrix) for sparse matrix operations and the GPSR (Gradient Projection for Sparse Reconstruction) algorithm for efficient signal recovery. The implementation involves key MATLAB functions for matrix transformations and optimization routines, including wavelet decomposition for sparse representation and convex optimization techniques for reconstruction. Furthermore, we analyze the program's performance metrics, practical applications in video compression, and future development prospects of this technology in modern video coding systems.

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