Dictionary design and disparity interpolation on distributed compressed sensing for light field image

Abstract

This paper discusses two terms of distributed compressed sensing for multi-view point images generated with a light field camera. Our first discussion is on the performance of dictionary designed with ADMM (Alternating Direction Method of Multipliers) and that of K-SVD since reconstructed image quality depends on the dictionary. The second discussion is disparity interpolation of non-key frames. The interpolation accuracy contributes to reconstructed image quality and effective dictionary design. Then, this paper compares three disparity interpolation methods: the overlapped block matching, the conventional optical flow, and the TVL1-optical-flow. Experimental results show that the dictionary design with ADMM is faster than that with K-SVD whereas PSNR values using ADMM are slightly lower than those of K-SVD, and the TVL1-optical flow is the fastest holding the highest PSNR values.