Finger Vein Image Denoising Based on Compressive Sensing
To extract venous information from noise-added images acquired by infrared sensor, in this paper, we presents a compressive sensing (CS) based application -- gradient projection for sparse reconstruction (GPSR) -- to reduce noise in synthetic vein images and real finger vein images respectively. Then compares the result with the reconstruction by wavelet threshold denoising algorithm. The results show that the GPSR has better performance than the wavelet threshold method in reducing noise, avoids losing the edge information of finger vein, and thus provides more accurate information for vein recognition and extraction.