CFP last date
20 January 2025
Reseach Article

Image Deblurring using Segmentation

by Johar A., Johar Aditi, Kalra G S
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 17
Year of Publication: 2014
Authors: Johar A., Johar Aditi, Kalra G S
10.5120/16428-6093

Johar A., Johar Aditi, Kalra G S . Image Deblurring using Segmentation. International Journal of Computer Applications. 93, 17 ( May 2014), 19-22. DOI=10.5120/16428-6093

@article{ 10.5120/16428-6093,
author = { Johar A., Johar Aditi, Kalra G S },
title = { Image Deblurring using Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 17 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number17/16428-6093/ },
doi = { 10.5120/16428-6093 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:16:00.276109+05:30
%A Johar A.
%A Johar Aditi
%A Kalra G S
%T Image Deblurring using Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 17
%P 19-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Motion deblurring is a vastly used technique in image processing and is an interesting task in this field . In this paper an algorithm is proposed for the performance of segmentation to create boundaries of the object under observation. Segmentation of the image is performed to separate the focused object from the blurred background. The image is uniformly blurred by performing kernel estimation of the background image and convoluting it with the focused part of the image. Finally deconvolution is performed on the image in order to obtain a clear image.

References
  1. Jun Xie1, Weiyao Lin1*, Hongxiang Li2, Kai Guo1, Bin Jin1, Yihao Zhang1, Donghua Liu3," A New Algorithm for Improving Deblurring Effects and Addressing Spatially-variant Blur Problems for Image Motion Deblurring", 2011 4th International Congress on Image and Signal Processing, pp. 651-655,2011.
  2. Qi Shan, Wei Xiong, and Jiaya Jia ," Rotational Motion Deblurring of a Rigid Object from a Single Image", IEEE transaction on image processing,2007.
  3. Ioannis M. Stephanakis and George C. Anastassopoulos,"Segmentation using adaptive thresholding on image histogram according to the incremental rates of the segment likelihood functions. "
  4. Deshpande, Ashwini M. ; Patnaik, Suprava, "On improving accuracy of PSF estimation in spectral and cepstrum domain with morphological filtering," Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN), 2012 1st International Conference on , vol. , no. , pp. 1,6, 19-21 Dec. 2012.
  5. Jeong Ho Lee, Member, "Image Deblurring by Using The Estimation of PSF Parameters for Image Devices", IEEE transaction on image processing,2010
  6. D. Kundur and D. Hatzinakos, "Blind image deconvolution," IEEE Signal Processing Magazine, pp. 61-63, 1996.
  7. Y. Yitzhaky and N. Kopeika, "Identification of blur parameters from motion blurred images," Graphical Models and Image Processing, vol. 59, no. 5, pp. 310-320, 1997.
  8. Cho, S. , Lee, S," Fast motion deblurring", ACM transactions on Graphics, vol. 28, no. 5, 2009.
  9. M. Dobes, L. Machala, and T. Furst, "Blurred image restoration: A fast method of finding the motion length and angle," Digital Signal Processing, vol. 20, pp. 1677-1686, 2010.
  10. X. Jiang, "Adaptive local thresholding by verification-based multithresh-old probing with application to vessel detection in retinal images," IEEE Trans. on Pattern Anal. and Machine Intell, vol. 25, No. 1, pp. 131-137, Jan. 2003.
  11. F. Yan, H. Zhang, C. R. Kube, "A multistage adaptive thresholding method," Pattern Recognition Letters, vol. 26, pp. 1183-1191, 2005.
  12. Johar A. , KalraGS. ,"Image deblurring using saliency detection", Proceedings of 2014 RAECS UIET Panjab University Chandigarh, pp. 1-4, 2014
Index Terms

Computer Science
Information Sciences

Keywords

Segmentation Cepstrum Inverse filtering