In the work, raw CFA image data is acquired in conjunction with 3-axis acceleration data using a custom-built imaging system. The raw image data records the redistribution of light but is effected by camera motion and the rolling shutter mechanism. Through the use of acceleration data, the spread of light to neighboring pixels can be determined. We propose a new approach to jointly perform deblurring and demosaicking of the raw image. This approach adopts edge-preserving sparse prior in a MAP framework. The improvements brought by our algorithm is demonstrated by processing the data collected from the imaging system.
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Ruiwen Zhen, Robert L. Stevenson, "Joint deblurring and demosaicking of CFA image data with motion blur," Proc. SPIE 9029, Visual Information Processing and Communication V, 90290B (17 February 2014);