Dictionary Construction Method for Image Training
An image training-based dictionary construction method suitable for building basis matrices in compressed sensing applications
Compressive Sensing Image Reconstruction Algorithm
A self-developed compressive sensing image reconstruction algorithm for educational purposes, implementing sparsification, observation coefficient processing, and final image reconstruction
Compressive Sensing: Wavelet-Based Sparsification with OMP Algorithm for Reconstruction and Recovery
Compressive sensing is an emerging and critically important discipline. This resource presents the most classic and straightforward framework from Hong Kong University's Sha Wei, implementing wavelet-based sparsification followed by Orthogonal Matching Pursuit (OMP) algorithm for signal reconstruction and recovery.
Signal Recovery in Compressed Sensing Theory
This code implements signal recovery in compressed sensing theory by transforming it into a regression problem with parameter constraints. Through Bayesian parameter estimation techniques, it achieves efficient reconstruction of sparse signals. The implementation includes key components for optimization algorithms and sparse modeling.
Radar One-Dimensional Range Profile Imaging Using SBL Algorithm and Kalman Filter Compressed Sensing
Implementation of radar one-dimensional range profile imaging using Sparse Bayesian Learning (SBL) algorithm and Kalman filter-based compressed sensing, followed by comparative analysis of their imaging performance characteristics.
Simulation of Channel Estimation Using Compressed Sensing
Compressed sensing-based channel estimation simulation code with IEEE publication, featuring sparse signal recovery algorithms and measurement matrix implementations
Bayesian Compressive Sensing and Source Code Implementation
IEEE Literature on Bayesian Compressive Sensing with Complete Source Code Implementation and Algorithm Explanations
Image Processing with Compressed Sensing and Wavelet Transform
Program implementations for image processing and image fusion based on compressed sensing and wavelet transform, featuring algorithms for multi-source image integration and quality enhancement
A Highly Typical Gradient Projection Algorithm in Compressed Sensing
A very typical gradient projection algorithm in compressed sensing that achieves exceptionally fast computational speeds, suitable for high-performance signal reconstruction applications.
Application of Compressed Sensing in Training Sequence-Based Channel Estimation with Implementation Details
This code demonstrates how compressed sensing is applied to training sequence-based channel estimation, showcasing the complete compression and reconstruction process with algorithm explanations.