DeepAI
Log In Sign Up

Blind Deconvolution Method using Omnidirectional Gabor Filter-based Edge Information

05/03/2019
by   Trung Dung Do, et al.
0

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.

READ FULL TEXT

page 3

page 5

page 6

11/17/2018

Edge-Based Blur Kernel Estimation Using Sparse Representation and Self-Similarity

Blind image deconvolution is the problem of recovering the latent image ...
09/07/2016

Guided Filter based Edge-preserving Image Non-blind Deconvolution

In this work, we propose a new approach for efficient edge-preserving im...
02/01/2022

Blind Image Deconvolution Using Variational Deep Image Prior

Conventional deconvolution methods utilize hand-crafted image priors to ...
05/29/2015

Improving Time Estimation by Blind Deconvolution: with Applications to TOFD and Backscatter Sizing

In this paper we present a blind deconvolution scheme based on statistic...
01/01/2018

Quality assessment metrics for edge detection and edge-aware filtering: A tutorial review

The quality assessment of edges in an image is an important topic as it ...
02/03/2012

Wavelet-based deconvolution of ultrasonic signals in nondestructive evaluation

In this paper, the inverse problem of reconstructing reflectivity functi...