Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Blur video restoration using Blind Deconvolution Method

Author : Sangareddy B K 1 Manasa T K 2

Date of Publication :15th May 2019

Abstract: Instability in the atmosphere and incompatibility camera settings leads to blurring of video. Closed circuit television [CCTV] is most commonly used for security purpose in homes, banks, hospitals, business, criminal investigation and colleges. Usually these cameras have resolution of 704x480 and 720x480. Even IR cameras are playing important role in industries these days. The IR cameras usually have a low resolution mostly 160x120 and 320x240 for technical reasons. In this case Image Processing is one of the boons for business, engineers, forensics and medical field to extract the required values from the image data. This paper introduces an effective method to deblur low resolution images. Blind Deconvolution method is applied to low resolution images. Then, restored gray images are converted into RGB images and write each RGB frame into the videoobject to make a video. The experimental results depict a high resolution video which is the sharpen form of low resolution video.

Reference :

    1. S. Cho & S. Lee: “Fast Motion Deblurring,” Transactions on Graphics (SIGGRAPH), Vol. 28, No. 5, pp. 1–145:8, 2009.
    2. Deepa Kundur, Student Member, and Dimitrios Hatzinakos, “A Novel Blind Deconvolution Scheme for Image Restoration Using Recursive Filtering”, IEEE Transactions On Signal Processing, Vol. 46, no. 2, February 1998.
    3. Punam Patil & R.B.Wagh “Implementation of Restoration of Blurred Image Using Blind Deconvolution Algorithm” IEEE 2013.
    4. Samarasinghe P.D, Kennedy R.A, “Blind deconvolution of natural images using segmentation based CMA,” IEEE, Signal Processing and Communication Systems (ICSPCS), pp.1-7, 2010.
    5. Pratibha Sharma, Jitendra Kumar “Blind Deconvolution Deblurring Technique in Image Processing”, International Journal for Research in Applied Science and Engineering Technology Volume.2 Issue IX, September 2014 ISSN: 2321-9653I.
    6. Minu Poulose “Literature Survey on Image Deblurring Techniques”, International Journal of Computer Applications Technology and Research Volume 2– Issue 3, 286 - 288, 2013.
    7.  A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, “Understanding and evaluating blind deconvolution algorithms”, in Proc. IEEE CVPR, Aug. 2009, pp. 1964– 1971.
    8. Ajita Bundela, Ankur Chourasiya, Uday Bhan Singh: “Restoration of Single Blur Image Using Blind Deconvolution Method”, International Journal of Engineering Trends and Technology (IJETT) – Volume 20 Number 2 – Feb 2015.
    9. M. Ramesh Kanthan & Dr. S. Naganandini Sujatha: “Blur Removal using Blind Deconvolution and Gradient Energy”, 978-1-5090-0612-0/16/$31.00 ©2016 IEEE.

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