Contrast-enhanced microscopic imaging of Malaria parasites

Abstract

This paper proposes an efficient algorithm for contrast enhancement to preserve the essential details of microscopic images of malaria infected blood using Gamma Equalization (GE). The central idea of this method is first, to convert the input color blood image into gray scale one, and then to calculate the range value for the γth order image of a gray scale image. The look-up-table (LUT) values are calculated and the gray scale image pixel intensity values are converted into LUT values which yield final contrast-enhanced image by retaining the essential details. We tested different values of gamma (γ). The value of γ = 0.8 yields maximum contrast enhanced image, which is very useful for image analysis and a computer aided diagnostic system for malaria. On comparison, GE is found to be better than Histogram equalization (HE), Imadjust (IA) and Contrast-limited adaptive histogram equalization (CLAHE) for microscopic blood images of malaria by using image quality measures: Absolute mean Brightness error (AMBE), Entropy and average luminance.