A novel retinex based approach for image enhancement with illumination adjustment

• Published in: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 1190 - 1194
• Main Authors: Xueyang Fu, Ye Sun, Minghui LiWang, Yue Huang, Xiao-Ping Zhang, Xinghao Ding
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2014
• Subjects: alternating direction optimization; Color; Computational modeling; Histograms; illumination adjustment; Image edge detection; Image enhancement; Lighting; retinex; variational framework
• ISSN: 1520-6149; 2379-190X
• DOI: 10.1109/ICASSP.2014.6853785

Retinex based algorithms have been widely used among in image enhancement. Since many retinex based algorithms remove illumination and regard the reflectance as enhancement, over-enhancement and unnaturalness are inevitable. In this paper, a novel retinex based image enhancement using illumination adjustment is proposed. Different from existing variational retinex models, a new model without the logarithmic transformation is established and can well preserve the edge. A fast alternating direction optimization method is used to solve this problem. After the decomposition of illumination and reflectance, a simple and effective post-processing method for illumination adjustment is adopted for the enhancement to make the result more natural. The proposed method can deal with many kinds of image, such as high dynamic range (HDR) images and non-uniform illumination images. Experimental results illustrate that the naturalness can be preserved while details are enhanced by the presented new approach.