Comparative analysis of fundus image enhancement in detection of diabetic retinopathy

This paper presents a comparative analysis of fundus image enhancement techniques to detect diabetic retinopathy (DR). Medical images frequently suffers from non-uniform illumination, poor contrast and noise, thus these images have to go through pre-processing stage. For image enhancement many techniques are proposed based on spatial domain (histogram). However, these methods usually decline to produce suitable consequences for non-uniform illumination and wide-ranging of low-contract. The comparative analysis and performance evaluation of various enhancement techniques will help in choosing most suitable technique which may significantly improve the detection of diabetic retinopathy. In this paper histogram equalization (HE), adaptive histogram equalization (ADHE), contrast limited adaptive histogram equalization (CLAHE) and exposure based sub-image histogram equalization (ESIHE) techniques are compared for pre-processing of fundus image for detecting DR. For fair analysis of these techniques, histogram, SNR, entropy, absolute mean brightness error and peak signal-to-noise ratio (PSNR) of fundus images are analyzed by using MATLAB.