papers AI Learner
The Github is limit! Click to go to the new site.

Blind Deconvolution Method using Omnidirectional Gabor Filter-based Edge Information

2019-05-03
Trung Dung Do, Xuenan Cui, Thi Hai Binh Nguyen, Hakil Kim, Van Huan Nguyen

Abstract

In the previous blind deconvolution methods, de-blurred images can be obtained by using the edge or pixel information. However, the existing edge-based methods did not take advantage of edge information in ommi-directions, but only used horizontal and vertical edges when recovering the de-blurred images. This limitation lowers the quality of the recovered images. This paper proposes a method which utilizes edges in different directions to recover the true sharp image. We also provide a statistical table score to show how many directions are enough to recover a high quality true sharp image. In order to grade the quality of the deblurring image, we introduce a measurement, namely Haar defocus score that takes advantage of the Haar-Wavelet transform. The experimental results prove that the proposed method obtains a high quality deblurred image with respect to both the Haar defocus score and the Peak Signal to Noise Ratio.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1905.01003

PDF

http://arxiv.org/pdf/1905.01003


Similar Posts

Comments