FASTICA based denoising for single sensor Digital Cameras images

t: Digital color cameras use a single sensor equipped with a color filter array (CFA) to capture scenes in color. Since each sensor cell can record only one color value, the other two missing components at each position need to be interpolated. The color interpolation process is usually called color demosaicking (CDM). The quality of demosaicked images is degraded due to the sensor noise introduced during the image acquisition process. Many advanced denoising algorithms, which are designed for monochromatic (or full color) images, are not directly applicable to CFA images due to the underlying mosaic structure of CFAs. A well designed deoising scheme can have advantages such as less noise-caused color artifacts and costeffective implementation. In this paper, a comparison of independent component analysis and principal component analysis for denoising single sensor Digital Cameras image is proposed. Simulation result of CFA images shows that independent component analysis provide much better denoising effect and peak signal-noise ratio in terms of both objective measurement and visual evaluation in comparison to principal component analysis(PCA).