Title :
CFA-based motion blur removal using long/short exposure pairs
Author :
Lasang, Pongsak ; Ong, Chin Phek ; Shen, Sheng Mei
Author_Institution :
Media Process. Group (MPG), Panasonic Singapore Labs. (PSL), Singapore, Singapore
fDate :
5/1/2010 12:00:00 AM
Abstract :
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.
Keywords :
Cameras; Colored noise; Deconvolution; Filters; Kernel; Motion detection; Noise robustness; Object detection; Pixel; Sensor arrays; Motion blur, color filter array (CFA), sensor noise modeling, HDR imaging, image alignment;
Journal_Title :
Consumer Electronics, IEEE Transactions on
DOI :
10.1109/TCE.2010.5505936