Real color image enhancement based on the spectral sensitivity of most people vision and stationary wavelet transform

Because the most algorithms of real color image enhancement did not relate to the spectral sensitivity of most people vision, the color restoration functions of some real color image enhancement algorithms are greatly at random and not proved , and the enhanced real color images which are based on illumination-reflectance model have the loss of details and the ‘halos’, we proposed a new algorithm to overcome these disadvantages. Firstly, we transform the real color image from RGB space to HSV space which is approximately orthonormal between the color and the value. Secondly, the illumination and the reflectance of the value are separated based on a new illumination-reflectance model described by stationary wavelet transform. We have obtained the conclusion that the illumination of image is mainly preserved in the low frequency part of stationary wavelet decomposition and the reflectance is mainly preserved in the high frequency parts. Thirdly, the dynamic range of illumination is compressed by Gaussian filtering. Lastly, the energy of the saturation of real color image in HSV space is attenuated according to the spectral sensitivity of most people vision. Experiments show that the color of image enhanced adapts well to the most people vision and is not obviously distorted, the preservation of the details is excellent and the ‘halos’ is effectively restrained. Real color image enhanced by the algorithm is much better than by the multi-scales Retinex's with color restoration (MSRCR).