LAUSR

This paper proposes compressive sampling (CS) framework for color retinal image (CRI) compression, which relies on spread spectrum Fourier sampling (SSFS) and total variant (TV)-based reconstruction method with three loop of RGB color space, referred to as RGB-TV. In CS, two steps of process are performed, i.e., compression and CS reconstruction. In compression steps, SFFS is performed to get compressed signal from original CRI with a high compression ratio (CR). While in CS reconstruction, TV-norm and TV proximal operator are exploited for problem optimization to recover original CRI from a compressed signal. In addition, signal-to-noise ratio (SNR), structural similarity (SSIM), and processing time are investigated for the performance metrics of the proposed RGB-TV. The computer simulation result shows that the proposed RGB-TV with a set of CRI of size 512 by 512 can compressed until CR = 10 which obtains mean SNR 22 dB, SSIM 0.84, and processing time 2.2 seconds.