Open AccessIdentification of Suitable Contrast Enhancement Technique for Improving the Quality of Astrocytoma Histopathological Images.
Author(s) -
Fahmi Akmal Dzulkifli
Publication year - 2021
Publication title -
elcvia. electronic letters on computer vision and image analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.15
H-Index - 11
ISSN - 1577-5097
DOI - 10.5565/rev/elcvia.1256
Subject(s) - adaptive histogram equalization , contrast (vision) , contrast enhancement , computer science , artificial intelligence , computer vision , histogram equalization , image enhancement , visibility , edge enhancement , brightness , image quality , sample (material) , pattern recognition (psychology) , histogram , image (mathematics) , optics , medicine , radiology , magnetic resonance imaging , chemistry , physics , chromatography
Contrast enhancement plays an important part in image processing. In histology, the application of a contrast enhancement technique is necessary since it can help pathologists in diagnosing the sample slides by increasing the visibility of the morphological and features of cells in an image. Various techniques have been proposed to enhance the contrast of microscopic images. Thus, this paper aimed to study the effectiveness of contrast enhancement techniques in enhancing the Ki67 images of astrocytoma. Three contrast enhancement techniques consist of contrast stretching, histogram equalization, and CLAHE techniques were proposed to enhance the sample images. The performance of each technique was compared by computing seven quantitative measures. The CLAHE technique was preferred for enhancing the contrast of the astrocytoma images. This technique produces good results especially in contrast enhancement, edge conservation and enhancement, brightness preservation, and minimum distortions to the enhanced images.