A fast Multi-Scale Retinex algorithm for color image enhancement

AbstractIn the state of the art, grayscale image enhancement algorithms are typically adopted for enhancement of RGB color images captured with low or non-uniform illumination. As these methods are applied to each RGB channel independently, imbalanced inter-channel enhancements (color distortion) can often be observed in the resulting images. On the other hand, images with non-uniform illumination enhanced by the retinex algorithm are prone to artifacts such as local blurring, halos, and over-enhancement. To address these problems, an improved RGB color image enhancement method is proposed for images captured under non-uniform illumination or in poor visibility, based on weighted guided image filtering (WGIF). Unlike the conventional retinex algorithm and its variants, WGIF uses a surround function instead of a Gaussian filter to estimate the illumination component; it avoids local blurring and halo artifacts due to its anisotropy and adaptive local regularization. To limit color distortion, RGB images are first converted to HSI (hue, saturation, intensity) color space, where only the intensity channel is enhanced, before being converted back to RGB space by a linear color restoration algorithm. Experimental results show that the proposed method is effective for both RGB color and grayscale images captured under low exposure and non-uniform illumination, with better visual quality and objective evaluation scores than from comparator algorithms. It is also efficient due to use of a linear color restoration algorithm.

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Color Image Enhancement Using a Retinex Algorithm with Bilateral Filtering for Images with Poor Illumination

Journal of Korea Multimedia Society ◽

10.9717/kmms.2016.19.2.233 ◽

2016 ◽

Vol 19 (2) ◽

pp. 233-239 ◽

Cited By ~ 1

Author(s):

Agustien Mulyantini ◽

Heung-Kook Choi

Keyword(s):

Image Enhancement ◽

Color Image ◽

Bilateral Filtering ◽

Color Image Enhancement ◽

Retinex Algorithm

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Improved Multi-Scale Retinex Approaches for Color Image Enhancement

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.39.32 ◽

2010 ◽

Vol 39 ◽

pp. 32-37 ◽

Cited By ~ 1

Author(s):

Min Yun Zhu ◽

Feng Su ◽

Wu Jing Li

Keyword(s):

Image Enhancement ◽

Color Image ◽

Experimental Results ◽

Color Channel ◽

Multi Scale ◽

Color Image Enhancement ◽

Single Scale ◽

Color Restoration

In this paper, an improved multi-scale Retinex with color restoration is proposed by correcting some distortion on color rendition. By using the proposed method, results of image enhancement are obtained and compared further with those acquired by employing the single-scale Retinex, the multi-scale Retinex and the conventional multi-scale Retinex with color restoration. For HSV space shows better color channel independence by comparison with RGB space, a multi-scale Retinex in HSV space is given out and explored to enhance images. The experimental results do show distinct information and effects.

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Color Image Enhancement Methods Based on Matlab

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.300-301.1664 ◽

2013 ◽

Vol 300-301 ◽

pp. 1664-1668

Author(s):

Xiao Min Xie ◽

Chang Ming Wang ◽

Ai Jun Zhang

Keyword(s):

Image Enhancement ◽

Color Image ◽

Histogram Equalization ◽

Human Vision ◽

Related Concept ◽

Multi Scale ◽

Color Image Enhancement ◽

Time Simulation ◽

Color Restoration ◽

Simulation Results

The aim of the paper is to provide three enhancement methods for processing color images, including: RGB Histogram equalization, the method based on HSI and Multi-scale Retinex with color restoration (MSRCR). Firstly, we shall briefly introduce color image enhancement and related concept. Then, emphasis is placed on the principle of the three methods. Afterwards, we make comparison among the three methods. Finally, we can get a conclusion that: MSRCR greatly not only strengthens the details but also keep the color of the original image and acts more consistent with characteristics of human vision. However, it takes longer time. Simulation results provide a guidance and reference for the choice of color image enhancement methods.

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