Comparative Analysis Between PCA and Fast ICA Based Denoising of CFA Images for Single-Sensor Digital Cameras
Denoising of natural images is the fundamental and challenging research problem of Image processing. This problem appears to be very simple however that is not so when considered under practical situations, where the type of noise, amount of noise and the type of images all are variable parameters, and the single algorithm or approach can never be sufficient to achieve satisfactory results. Single-sensor digital color cameras use a process called color demosaicking to produce full color images from the data captured by a Color Filter Array (CFA). Normally the quality of images are degraded because of sensor of camera. In this paper, the authors have developed PCA, FASTICA based algorithm with K-means clustering and compared the both.