Bilateral tone mapping scheme for color correction and contrast adjustment in nearly invisible medical images

Medical images are commonly used to diagnose and screen various diseases. However, medical images taken by operators with different skill levels have a considerable variation in visual quality. Poor illumination of images increases uncertainty in clinical treatment and lead to the risk of misdiagnosis. This paper proposes a novel bilateral tone-mapped gamma correction to enhance the visual quality of medical images without affecting the natural color quality. First, the proposed tone-mapped gamma correction is employed to enhance the intensity values of poorly illuminated medical images. Then, bilateral enhancement curve adjustment is performed to effectively improve the global luminance content of the input image with features and richer information. The image quality assessment measures like entropy, blind/reference less image spatial quality evaluator, natural image quality evaluator, perception-based image quality evaluator, contrast enhancement based image quality parameter, and color contrast fog density evaluates the superior performance of the proposed technique. The experimental results significantly enhance the intensity difference between dark and bright areas and can aid clinical experts and intelligent health fields.