Dynamic color image resolution compensation under low light

In low light environment, the dynamic color images are poorly identified. Therefore, this paper puts forward a kind of contrast resolution compensation algorithm. This algorithm is based on human visual perception model. Firstly, a color image is transformed from RGB color space into HSV color space, component of vector H remain unchanged; Secondly, extracting image feature parameters of vector V, then using contrast resolution compensate component of vector V in order to enhance image brightness; Thirdly, the component of vector S is linear stretched in order to recover the image color information; Finally, using the treated V elements, treated component of vector S and untreated component of vector H contracture a new enhanced image with RGB color space by inverse transform. Compared with histogram equalization and γ transformation algorithms, the compensation method can enhance images and improve image quality, and the compensated image has smaller color deviation. Using the quality assessment function of color image (CAF), the value of CAF with the compensated image is maximum, and the assessment result keeps consistent with the subjective assessment. This results show that the method is feasible with dynamic color image resolution compensation under low light.