Performance comparative study on PCA based denoising with Joint Demosaicing & denoising

In general digital camera uses a single-chip image sensor, with spectrally shifted alternating patterns of three or more color filters applied to each pixel location called color filter array. Digital cameras with single sensor use demosaicing to fabricate full color images from the data captured by a color filter array (CFA). The goodness of demosaiced images is subject to influences from noise in the image sensor during the image capturing process. In order to reduce the noise the conventional solution like Joint Demosaicing and denoising may be adopted, that combines both demosaicing and denoising procedures in to a single operation. Another method, Total least square denoising method is also used to improve image quality. But, In PCA based spatially adaptive denoising of CFA, images uses the concept of denoising first and demosaicing later for reducing the noise. It has some advantages such as less noise-caused color artifacts and cost-effective implementation. When compared to Joint Demosaicing and denoising, PCA Based spatially adaptive denoising of CFA Images is more effective in reducing the noise in terms of both objective measurement and visual evaluation. This method effectively suppresses noise while preserving color edges and details. The direct CFA image denoising scheme, followed by a succeeding demosaicing scheme reduces extensively the noise-caused color artifacts in the demosaiced images. Such artifacts often appear in the output full-color images of many demosaicing first and denoising later schemes, as well as joint demosaicing- denoising schemes. The CPSNR ratio is much better, when compared to Joint demosaicing and denoising schemes by preserving the structures in the image which are often smoothed by other denoising schemes.