Compressive Sampling of Color Retinal Image Using Spread Spectrum Fourier Sampling and Total Variant

Abstract

In medical imaging, the application of retinal images demands a lot of retinal photos to analyze and requires efficient compression techniques for retinal image storage. Retinal images must meet stringent quality requirements for clinical data to be accurate and dependable. This paper proposes a 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 loops of RGB color space, referred to as RGB-TV. In CS, two procedures are performed, i.e., compression and CS reconstruction. In compression steps, SFFS is performed to get a compressed signal from the 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 reconstruction 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 pixels can compress until CR = 10 which obtains mean SNR of 22 dB, SSIM 0.84, and reconstruction time of 2.2 seconds.