Enhancement of Microscopic Images Using K-Means Segmentation Based on Adaptive Histogram Equalization

Micrograph is a technique of taking magnified light images of small objects, usually using a microscope. Microscopy is used to investigate the nature of matter in many branches of science, including biology, forensic science, stratigraphy, medicine, and mining. The enhancement of medical microscopic images is crucial to medical imaging branches. However, microscopic images sometimes suffer from a lack of contrast. This paper aimed to enhance microscopic images on the basis of K-means Segmentation Adaptive Histogram Equalization (KSAHE). Afterward, the k-means method was used to segment images into several areas. With the color compounds separated from achromatic ones based on the HSV color space, the proposed algorithm was compared with several other algorithms. Results illustrated that the proposed method has considerably good quality metrics in terms of the mean of entropy (7.913), value of average gradient (14.473), and mean of standard deviation (61.049).