Explore MATLAB source code curated for "稀疏基" with clean implementations, documentation, and examples.
Image compressive sensing implementation using FFT (constructing orthogonal transformation matrix) or DWT (measuring high-frequency coefficients) as sparsity bases, with Orthogonal Matching Pursuit (OMP) algorithm for reconstruction
Simulation of a typical compressed sensing program using wavelet basis as the sparse representation and Orthogonal Matching Pursuit (OMP) as the reconstruction algorithm, with implementation details on signal sparsification and iterative recovery.
Computational methods for determining Restricted Isometry Property (RIP) factors of measurement matrices and sparsity bases in compressed sensing systems, with implementation considerations.
Using wavelet transform as the sparse basis and Orthogonal Matching Pursuit (OMP) algorithm for image reconstruction, this approach addresses computational intensity through improved block-wise processing to significantly reduce imaging time while maintaining reconstruction quality.
Image Compressed Sensing Using Orthogonal Matching Pursuit Algorithm with Sparse Representation Techniques