CFA-based motion blur removal using long/short exposure pairs

This paper presents an efficient and effective motion blur removal method based on long and short exposure images. The two images are captured sequentially and motion pixels between the images are then robustly detected, with suppression of noise and prevention of artifacts around object boundaries. Object motion blur is removed and high quality image is obtained by merging the two images with taking into account the detected motion pixels. The proposed method is directly performed on the CFA (Color Filter Array) image which only has one color component per pixel. It has low computational complexity and low memory requirements. The proposed method also achieves a HDR (High Dynamic Range) image at the same time.