High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

A Review on Multi Scale Patch Based Image Restoration

Author(s):

Bhadane Bhupesh Sanjay , D.N.Patel COE Shahada,Nandurbar; Jayshree Hiralal Patil, D.N.Patel COE Shahada,Nandurbar

Keywords:

Image restoration, Deblurring

Abstract

Blind image restoration is used to in the Prior information of an image can often be used to restore the sharpness of edges. De-blurring is the process of removing blurring artefacts from images, such as blur caused by defocus aberration or motion blur. Motion blur is the apparent streaking of rapidly moving objects in a still image. A Gaussian blur is the result of blurring an image by a Gaussian function. The success of recent single-image methods partly stems from the use of various sparse priors, for either the latent images or motion blur kernels. De-blurring is the process of removing blurring artifacts from images, such as blur caused by defocus aberration or motion blur. Motion blur is the apparent streaking of rapidly moving objects in a still image. A Gaussian blur is the result of blurring an image by a Gaussian function. The success of recent single-image methods partly stems from the use of various sparse priors, for either the latent images or motion blur kernels. KSR also finds good kernel matrix approximation to speed up blurring and achieve good de-blur performances on digital datasets. As the unique identification of a vehicle, license plate is a key clue to uncover over-speed vehicles or the ones involved in hit-and-run accidents. We evaluate our approach on real-world images and compare with several popular state-of-the-art blind image de-blurring algorithms. Experimental results demonstrate the superiority of our proposed approach in terms of effectiveness and robustness.

Other Details

Paper ID: IJSRDV8I10365
Published in: Volume : 8, Issue : 1
Publication Date: 01/04/2020
Page(s): 90-92

Article Preview

Download Article