Compressed Sensing for Image Super-Resolution Reconstruction

Application Background: This code implementation is simplified for introductory learning purposes. It demonstrates core compressed sensing principles through minimal viable examples. Key Technology: Image super-resolution reconstruction using compressed sensing methodology, incorporating DWT (Discrete Wavelet Transform) for sparse representation and inverse wavelet transform for reconstruction. The implementation showcases how to achieve resolution enhancement while maintaining image quality through sparse optimization techniques.