Fast image enhancement based on color space fusion

The current Retinex algorithm processes the RGB channels separately for color image enhancement. However, it changes the ratios of RGB components and also causes some serious problems, such as color distortion, color noise, and the halo artifacts. To solve these issues, we propose a novel algorithm based on color space fusion. The single scale Retinex with fast mean filtering is applied to the luminance component in hue-saturation-value (HSV) color space. An enhancement adjustment factor is introduced to avoid color distortion and noise amplification. Then, the surrounding function is replaced by a small scale Gaussian filter in RGB color space to eliminate the halo artifact. A parameter is involved to keep the color natural when the reflection is estimated. Finally, the enhanced color image is constructed from the weighted averaging results of these two steps. The subjective and objective evaluations of many different backlight images captured by different cameras are implemented to verify the validity of the proposed algorithm in our experiments. The experimental results show that the proposed algorithm can not only significantly suppress the halo effect and noise amplification, but can also remove color distortion. Our proposed algorithm is superior to the multi-scale Retinex with color restoration approach and other state-of-the-art methods. (c) 2014 Wiley Periodicals, Inc. Col Res Appl, 41, 22-31, 2016