Image resolution and sharpness are essential criteria for a human observer when estimating the image quality. Typically cheap small-sized, low-resolution CMOS-camera sensors do not provide sharp enough images, at least when comparing to high-end digital cameras. Sharpening function can be used to increase the subjective sharpness seen by the observer. In this paper, few methods to apply sharpening for images captured by CMOS imaging sensors through color filter array (CFA) are compared. The sharpening easily adds also the visibility of noise, pixel-cross talk and interpolation artifacts. Necessary arrangements to avoid the amplification of these unwanted phenomenon are discussed. By applying the sharpening only to the green component the processing power requirements can be clearly reduced. By adjusting the red and blue component sharpness, according to the green component sharpening, creation of false colors are reduced highly. Direction search sharpening method can be used to reduce the amplification of the artifacts caused by the CFA interpolation (CFAI). The comparison of the presented methods is based mainly on subjective image quality. Also the processing power and memory requirements are considered.
In this paper, some arrangements to apply Noise Reduction (NR) techniques for images captured by a single sensor digital camera are studied. Usually, the NR filter processes full three-color component image data. This requires that raw Bayer-matrix image data, available from the image sensor, is first interpolated by using Color Filter Array Interpolation (CFAI) method. Another choice is that the raw Bayer-matrix image data is processed directly. The advantages and disadvantages of both processing orders, before (pre-) CFAI and after (post-) CFAI, are studied with linear, multi-stage median, multistage median hybrid and median-rational filters .The comparison is based on the quality of the output image, the processing power requirements and the amount of memory needed. Also the solution, which improves preservation of details in the NR filtering before the CFAI, is proposed.