Retinal image enhancement by index of fuzziness in multi-mode histogram

Evaluation of a retinal image is widely employed to help doctors diagnose many diseases, such as diabetes or hypertension. From acquisition process, retinal images often have low grey level contrast and dynamic range. This paper proposes histogram analysis for solving the problems of retinal image enhancement. The proposed method uses fuzzy set to enhance the images by partitioning the image histogram to multimodes with derivative equation. Each mode of the histogram is contrasted by finding the optimal crossover point of S-function with an index of fuzziness, which is designed for contrasting a field of view in the images. Our algorithm can achieve a number of properties of an importance for contrast stretching, such as compressed the noise in background and produced a high contrast in the field of view that provide feasibility in diagnosis from a retinal image.