JOURNAL ARTICLE

Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images

Shuhang WangJin ZhengHai‐Miao HuBo Li

Year: 2013 Journal:   IEEE Transactions on Image Processing Vol: 22 (9)Pages: 3538-3548   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Image enhancement plays an important role in image processing and analysis. Among various enhancement algorithms, Retinex-based algorithms can efficiently enhance details and have been widely adopted. Since Retinex-based algorithms regard illumination removal as a default preference and fail to limit the range of reflectance, the naturalness of non-uniform illumination images cannot be effectively preserved. However, naturalness is essential for image enhancement to achieve pleasing perceptual quality. In order to preserve naturalness while enhancing details, we propose an enhancement algorithm for non-uniform illumination images. In general, this paper makes the following three major contributions. First, a lightness-order-error measure is proposed to access naturalness preservation objectively. Second, a bright-pass filter is proposed to decompose an image into reflectance and illumination, which, respectively, determine the details and the naturalness of the image. Third, we propose a bi-log transformation, which is utilized to map the illumination to make a balance between details and naturalness. Experimental results demonstrate that the proposed algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images.

Keywords:
Naturalness Color constancy Computer science Computer vision Artificial intelligence Lightness Brightness Filter (signal processing) Image restoration Algorithm Image (mathematics) Image quality Image processing Mathematics Optics

Metrics

1580
Cited By
12.48
FWCI (Field Weighted Citation Impact)
35
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Color Science and Applications
Physical Sciences →  Physics and Astronomy →  Atomic and Molecular Physics, and Optics

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