Title: A method for blind image deblurring based on Gabor filter edge estimation

Authors: Van Huan Nguyen; Trung Dung Do; Xuenan Cui; Hakil Kim

Addresses: Faculty of Information Technology, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam ' Faculty of Information Technology, Le Quy Don Technical University, Hanoi, Vietnam ' Department of Information and Communication Engineering, Inha University, Incheon, South Korea ' Department of Information and Communication Engineering, Inha University, Incheon, South Korea

Abstract: Edge is widely used in blind deconvolution methods to provide the information source for the deblurring process. In the natural images, the blurring can be shown in any directions on edges randomly. However, the previous edge-based deconvolution methods made use of vertical and/or horizontal edge information only in the recovering process that lowers the performance. In this paper, a novel method of blind deconvolution using Gabor filter to estimate the edge information in omnidirectional directions is proposed. The deblurring process is then followed by applying fast iterative shrinkage-thresholding algorithm and iteratively reweighted least squares to recover the true sharp image. Also, the paper proposes a sharpness measurement, named as Haar defocus score, based on Haar-wavelet transformation, to estimate the quality of the deblurred image in cases no ground-truth exists for comparison. Experiments on the common public databases in the field show promising performance of the proposed method with respect to both PSNR and Haar defocus score measurements in comparison with the previous methods.

Keywords: blind deconvolution; omnidirectional edge; deblurring; Gabor filter.

DOI: 10.1504/IJIIDS.2021.116466

International Journal of Intelligent Information and Database Systems, 2021 Vol.14 No.3, pp.257 - 276

Received: 03 Aug 2020
Accepted: 24 Sep 2020
Published online: 26 Jul 2021 *

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