Blind Deconvolution Method using Omnidirectional Gabor Filter-based Edge Information
This work addresses image quality issues in blind deconvolution for applications like photography or medical imaging, but it is incremental as it builds on existing edge-based methods by extending directionality.
The paper tackles the problem of blind deconvolution in image deblurring by proposing a method that utilizes edge information in multiple directions, overcoming limitations of existing methods that only use horizontal and vertical edges. The results show high-quality deblurred images, as evidenced by improvements in the Haar defocus score and Peak Signal to Noise Ratio.
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.