EXTRACTION OF ORIGNAL IMAGE FROM BLURRED IMAGE USING DIFFERENT IMAGE PROCESSING TECHNIQUES
Author(s):
Sidhant Rana, Yash Seetha, Rishika Maiwal, S.U. Saoji
Keywords:
Particle filter; Image restoration; Photographic images; Motion blur; Sensor nonlinearity; Multiplicative noise; Non-Gaussian noise; Recursive Bayesian framework; Autoregressive process.
Abstract
The concept of restoring photographic images degraded by motion blur and film-grain noise is based on the one-dimensional particle filter, a new approach is proposed for restoration under space-invariant as well as spacevariant blurring conditions. The method works by propagating the samples of the chance distribution through associate acceptable state model. The weights of the samples are computed using the observation model and the degraded image. The samples and their corresponding weights are used to estimate the original image. In order to verify and validate the proposed approach, the method is tested on several images, both synthetic and real. All the other different techniques used are either too mainstream to use in image restoration process.
Article Details
Unique Paper ID: 148381

Publication Volume & Issue: Volume 6, Issue 1

Page(s): 803 - 806
Article Preview & Download




Publish book

Go To Issue



Call For Paper

Volume 6 Issue 2

Last Date 25 July 2019


About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:8200 61 5067
Email: editor@ijirt.org
Website: ijirt.org

Policies