Research Of Color Image Enhancement Algorithms

In recent years,the smart phone industry has flourished.The camera function,face recognition function,etc.have become the core technology of major mobile phone manufactures.Color image enhancement algorithms play an important role in these technologies.Due to insufficient lighting conditions,low illumination images are often appears and not only brings an uncomfortable visual feeling to human,but also is not beneficial for image analysis and comprehension and so on.To improve the quality of low illumination image,it needs to be enhanced.Therefore,in this paper,the low illumination images enhancement algorithm is studied deeply.The main idea of this paper is to convert the color image into the HSV(HSI)color space,separate the hue component,the saturation component and the luminance component.then extract the luminance component and enhance it,finally synthesize the processed luminance component and other components into a clear color image.This paper implements two algorithms that enhance the luminance component.While the V-system.a new orthogonal multi-wavelet,is introduced for the enhancement of the luminance component.First.we perform V-transform to the luminance to isolate the high,low frequency sub-bands.And then process Retinex adjustment to the low-frequency sub-band to reduce the influences of illumination to the image,while we use improved fuzzy enhancement to the high frequency sub-band to achieve image denoising and enhancement.Finally,the processed luminance component and other components are synthesized into a clear RGB image.Here is another algorithm.The luminance component are divided into high and low frequency sub-bands by DT-CWT.The high-frequency sub-band is processed by Butterworth filter to enhance the image details and suppress the noise while the low-frequency sub-band is managed by the improved tone mapping to adjust the image illumination.Finally.DT-CWT inverse transfromation is applied to obtain the reconstructed luminance component which is synthesize with other components to obtain a clear RGB iamge.A lot of experimental data show that the algorithm of this paper significantly improves the visual effect and quality of low illumination images and performs well in both subjective feelings of human eyes and multiple objective indicators,which proves the effectiveness of the proposed algorithm.