Compressive Sensing CS - Sparse Representation Using Wavelet Transform

Compressive Sensing CS implementation featuring wavelet transform for sparse representation, Gaussian random matrix as measurement matrix, and IRLS algorithm for reconstruction. Processes 256x256 Lena image, compares original image with IRLS reconstruction results at different sampling ratios (0.74, 0.5, 0.3), runs 50 trials each to evaluate algorithm performance through PSNR metrics and execution time analysis.