Structure-preserving contrast enhancement of fundus images using dualistic Sub-Image Bi-histogram bezier curve - Chia, Kelvin Hiik Ling; Yan, Chai Hum; Tan, Tian Swee; Wan Hazabbah Wan Hitam,; Muhammad Amir As’ari,; Abdul Asnida Wahab,; Jia, Hou Tan; Kah, Meng Leong; Sin, Joyce Yin Sia; Foh, Matthias Thye Tiong; Sameen Ahmed Malik,; Sinan S. Mohammed Sheet,; et al. (Penerbit Universiti Kebangsaan Malaysia, 2023)
Diabetic retinopathy is a common eye disease among diabetic patients which is caused by excessive sugar in the blood vessels that damage the retina. Fundus images are retina images that are captured and diagnosed by ophthalmologists. Ophthalmologists diagnose the progressive stages of diabetic retinopathy so that early detection of pre-diabetic retinopathy can be carried out. However, the quality of the fundus image can be associated with the brightness of the background and the indistinctive vessel contrast. This paper presents a novel extension of Bi-histogram Bezier curve contrast enhancement (BBCCE) based on the mean partition of its histogram. The disadvantage of having mean as the threshold partition is that the histogram distribution can be skewed due to an outlier. The proposed Dualistic Sub-Image Bi-histogram Bezier Curve Contrast Enhancement (DSI-BBCCE) method partitions the original histogram into two, using the median of the active dynamic intensity range of the input image and process two Bezier transform curves separately to replace the original cumulative density function curve as the median is not affected by the outlier. This DSI-BBCCE has the advantage of preserving the structure, median brightness and preventing over enhancement. The result shows that DSI-BBCCE has achieved a power signal to noise ratio (PSNR) of 20.08±0.94 dB, absolute mean brightness error (AMBE) of 20.15±1.89, structural similarity index model (SSIM) of 0.8096±0.0185, structure measure operator (SMO) of 3.2±1.10 and lightness measure order (LMO) of 200.90±44.19.