EXTRACTION OF ORIGNAL IMAGE FROM BLURRED IMAGE USING DIFFERENT IMAGE PROCESSING TECHNIQUES

  • Unique Paper ID: 148381
  • Volume: 6
  • Issue: 1
  • PageNo: 803-806
  • 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.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{148381,
        author = {Sidhant Rana and Yash Seetha and Rishika Maiwal and S.U. Saoji},
        title = {EXTRACTION OF ORIGNAL IMAGE FROM BLURRED IMAGE USING DIFFERENT IMAGE PROCESSING TECHNIQUES},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {1},
        pages = {803-806},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148381},
        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. },
        keywords = {Particle filter; Image restoration; Photographic images; Motion blur; Sensor nonlinearity; Multiplicative noise; Non-Gaussian noise; Recursive Bayesian framework; Autoregressive process. },
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 6
  • Issue: 1
  • PageNo: 803-806

EXTRACTION OF ORIGNAL IMAGE FROM BLURRED IMAGE USING DIFFERENT IMAGE PROCESSING TECHNIQUES

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