Performance Analysis of Compressive Sensing Algorithms for Image Processing
نویسندگان
چکیده
Compressive sensing is an emerging research field that has applications in signal processing, error correction, medical imaging, seismology, and many more other areas. Compressive sensing has a wide range of applications that include error correction, imaging, radar and many more. We present a new algorithm (the Modified Orthogonal Matching) for signal reconstruction in compressive sensing. We have given a basic frame work for our algorithm. This algorithm is able reconstructs the denoised Image efficiently. In addition we have compared the simulated results of BP with OPM and modified OMP with standard OMP in sense of PSNR and Computational Time. Simulation results show that the modified algorithm outperforms existing compressed sensing reconstruction methods.
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