摘要
To reduce the cost, size and complexity, a consumer digital camera usually uses a single sensor overlaid with a color filter array(CFA) to sample one of the red-green-blue primary color values, and uses demosaicking algorithm to estimate the missing color values at each pixel. A novel image correlation and support vector machine(SVM) based edge-adaptive algorithm was proposed, which can reduce edge artifacts and false color artifacts, effectively. Firstly, image pixels were separated into edge region and smooth region with an edge detection algorithm. Then, a hybrid approach switching between a simple demosaicking algorithm on the smooth region and SVM based demosaicking algorithm on the edge region was performed. Image spatial and spectral correlations were employed to create middle planes for the interpolation. Experimental result shows that the proposed approach produced visually pleasing full-color result images and obtained higher CPSNR and smaller S-CIELAB*ab?E than other conventional demosaicking algorithms.
To reduce the cost, size and complexity, a consumer digital camera usually uses a single sensor overlaid with a color filter array(CFA) to sample one of the red-green-blue primary color values, and uses demosaicking algorithm to estimate the missing color values at each pixel. A novel image correlation and support vector machine(SVM) based edge-adaptive algorithm was proposed, which can reduce edge artifacts and false color artifacts, effectively. Firstly, image pixels were separated into edge region and smooth region with an edge detection algorithm. Then, a hybrid approach switching between a simple demosaicking algorithm on the smooth region and SVM based demosaicking algorithm on the edge region was performed. Image spatial and spectral correlations were employed to create middle planes for the interpolation. Experimental result shows that the proposed approach produced visually pleasing full-color result images and obtained higher CPSNR and smaller S-CIELAB*ab?E than other conventional demosaicking algorithms.
基金
Projects(51174258,11105002)supported by the National Natural Science Foundation of China
Project(KJ2013B087)supported by Anhui Provincial Natural Science Research Projects in Central Universities,China
Projects(2011B31,2013A4017)support by the Guidance Science and Technology Plan Projects of Huainan,China
Project(2012QNZ06)supported by the Youth Foundation of Anhui University of Science&technology of China