Rear portion of the eye can be pictured by the retinal fundus imaging technique. The retinal fundus images provide clear description about the retinal blood vessels and optic disc regions. Most of the retinal diseases have perceptible symptoms on these regions and hence this can facilitate the optometrist for early diagnosis and treatment of retinal diseases. Blur, uneven illumination and poor contrast in the retinal fundus images are the commonly seen challenges for both manual and automated image analyzing systems. In this paper, a new method is proposed for the enhancement of uneven illuminance and contrast fundus images by adjusting their luminance and contrast based on Particle swarm optimization (PSO). The proposed method incorporating gamma correction on the HSV color space and contrast adjustment on the LAB color space. The contrast adjustment is optimized by the PSO algorithm to improve the enhancement process. The proposed method is evaluated on the publicly available databases DIARET DB0 and DIARET DB1. The Structural Similarity Index and Peak Signal to Noise Ratio are the performance measures used to evaluate the enhancement method. From the results obtained it is inferred that the fundus image with uneven illumination and contrast is enhanced in a better way by the proposed method.

眼睛的后部可以通过视网膜眼底成像技术成像。视网膜眼底图像清楚地描述了视网膜血管和视盘区域。大多数视网膜疾病在这些区域都有明显的症状，因此这有助于验光师对视网膜疾病进行早期诊断和治疗。视网膜眼底图像的模糊、光照不均匀和对比度差是手动和自动图像分析系统常见的挑战。在本文中，提出了一种基于粒子群优化（PSO）通过调整亮度和对比度来增强不均匀照度和对比度眼底图像的新方法。所提出的方法结合了对 HSV 颜色空间的伽马校正和对 LAB 颜色空间的对比度调整。通过PSO算法优化对比度调整以改进增强过程。所提出的方法在公开可用的数据库 DIARET DB0 和 DIARET DB1 上进行了评估。结构相似性指数和峰值信噪比是用于评估增强方法的性能指标。从得到的结果可以推断，所提出的方法以更好的方式增强了具有不均匀光照和对比度的眼底图像。