A study on the 3D-weighted filtering for the 1/f noise reduction on CMOS image sensor

We propose a new method for 1/f noise reduction in complementary metal oxide semiconductor image sensors (CMOS Image Sensors: CIS) by applying characteristics of noise distribution on time domain. The algorithm using time domain or stacking images which are focused on same pixel position are proposed to make up for the weakness of general method on edge region. Nevertheless, in the case of using of self-pixel position, some problems such as blocking effect or acquisition of images are occurred. In this study, we propose the algorithm 3D weighted filtering using multi-images through noise distribution. By using weight value on the center pixel of each 2D masks, the optimized algorithm is implemented. The purpose of proposed method is to obtain the best PSNR with minimum number of frame and minimum weight value. We have used White Gaussian noise distribution because 1/f noise has that distribution. Through the proposed algorithm, we have obtained the better PSNR than other methods as a masking method, Wiener filter and self pixel based method. The algorithm is expected that is effective for other random noise likes as photon shot noise with Poisson distribution.