Performance Optimization of Retinex–Based Image Enhancement Algorithm

• Main Authors: WU, WAN-JU, 吳宛儒
• Other Authors: YEA, CHING-WEI
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/b8kkxn

碩士 === 國立中正大學 === 電機工程研究所 === 105 === Image enhancement plays an important role in digital image processing and has been applied to fields of science and engineering. Among all of the image enhancement algorithms, Retinex-based algorithms are considered most effective in maintaining details of images. Despite the advantages, Retinex-based algorithms are generally more complex and consume considerably more time to maintain the balance between image detail and ambient illumination. And like most image enhancement algorithms, conventional Retinex-based algorithms are prone to over-enhancement when processing images with non-uniform illumination. To deal with aforementioned issues, various approaches are proposed and explored in the thesis. First, an optimized illumination estimation, which is the most time-consuming part of conventional Retinex-based algorithms, is proposed to reduce the time consumption. Furthermore, we propose an adaptive restoration process, which autonomously detects the brightest and darkest parts of the image and make modifications to the core algorithm accordingly to avoid over-enhancement. We also explored the possibility of hardware acceleration in the final chapter. It is hoped that the optimal performance can be achieved by the hardware and software co-design. Experimental results show that proposed Retinex-based algorithm can enhance details of images while preserving perceived naturalness without over-enhancement. And the execution time is greatly reduced.