Rotation-invariance can further improve state-of-the-art blind deconvolution techniques

Fernando Cervantes, Bryan Usevitch, Vladik Kreinovich
2016 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)  
In many real-life situations, we need to reconstruct a blurred image in situations when no information about the blurring is available. This problem is known as the problem of blind deconvolution. There exist techniques for solving this problem, but these techniques are not rotation-invariant. Thus, the result of using this technique may change with rotation. So, if we rotate the image a little bit, the method, in general, leads to a different deconvolution result. Therefore, even when the
more » ... nal reconstruction is optimal, the reconstruction of a rotated image will be different and, thus, not optimal. To improve the quality of image decomposition, it is desirable to modify the current stateof-the art techniques by making them rotation-invariant. In this paper, we show how this can be done, and we show that this indeed improves the quality of blind deconvolution.
doi:10.1109/smc.2016.7844614 dblp:conf/smc/CervantesUK16 fatcat:22hrivaxmjamhgrczm3im23odm