학술논문
Spatial-scale-based blur kernel estimation for blind motion deblurring
Document Type
Conference
Author
Source
2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Security, Pattern Analysis, and Cybernetics (SPAC), 2017 International Conference on. :256-261 Dec, 2017
Subject
Language
Abstract
Maximum a posteriori (MAP)-based single-image blind motion deblurring methods are extensively studied in the past years, and have achieved great progress. However, because of imperfect salient edges selection, most state-of-the-art methods still cannot estimate the blur kernel (BK) accurately, especially in large motion blur cases. In this paper, we propose a novel spatial-scale-based approach to estimate an accurate BK from a single motion blurred image by combining the spatial scale and L 0 norm. Furthermore, we propose an efficient optimization strategy which can solve the proposed model efficiently. Extensive experiments compared with state-of-the-art blind motion deblurring methods demonstrate the effectiveness of our method.