Adaptive Low-light Image Enhancement Algorithm Based on Principal Component Analysis
Aiming at the problems of low visibility,color degradation and noise of low-light images,etc.an adaptive low-light image enhancement algorithm based on principal component analysis is pro-posed.Firstly,the original RGB image is converted to HSV color space and the V component is extracted.Then the parameters of the adaptive brightness enhancement function is adjusted according to the esti-mated illumination component,and the V component of the image is enhanced by image fusion.Finally,the image is converted from HSV space back to RGB space.Experimental results show that the proposed algorithm retains the details of low-light images and balances image colors well.
万方数据
维普
