# Blind Deconvolution Method using Omnidirectional Gabor Filter-based Edge Information

## TL;DR

This paper introduces a blind deconvolution method that leverages omnidirectional Gabor filter-based edge information to improve image sharpness, utilizing multiple edge directions and a Haar defocus score for quality assessment.

## Contribution

It proposes a novel edge-based blind deconvolution technique using omnidirectional Gabor filters and introduces a Haar defocus score for better image quality measurement.

## Key findings

- Achieves higher deblurring quality as measured by Haar defocus score.
- Outperforms existing methods in Peak Signal to Noise Ratio.
- Utilizes multiple edge directions for improved image recovery.

## 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.

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Source: https://tomesphere.com/paper/1905.01003