Enhancement Algorithm of Color Fog Image Based on the Adaptive Scale and S-Cosine Curve

Abstract:

To deal with the image contrast and color fidelity details problem in the traditional Center around the Retinex image enhancement algorithms, Enhancement algorithm of color fog image based on the adaptive scale and s-cosine curve is proposed. Firstly, the image is transformed into the RGB color space. Then the each channel pixel values can be stretched the grayscale range by S-cosine curve and introduces the local correction function. It can calculate the scale of the Gaussian kernel, and then proceeds to do the Gamma correction for the estimates of the reflection component, obtains the multi-scale image by the weighted average. Afterwards, the obtained image is used to global nonlinear correction, image sharpening and smoothing, and being superimposed reflection components, achieving the image enhancement. At last, it can carry on the intensity adjustment and grayscale adjustment for the obtained image. Through the subjective observation and objective evaluation, this algorithm is better than the traditional center around Retinex algorithm and MSRCR algorithm in processing effect.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 3362-3367
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.3362
• Online since: February 2014
• Authors: Yin Gao, Li Jun Yun*, Jun Sheng Shi, Fei Yan Cheng
• Keywords: Adaptive Scale, Brightness Adjustment, Gamma Correction, Image Enhancement, s-Cosine Curve

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