CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Survey on Blurred Images with Restoration and Transformation Techniques

by Rohina Ansari, Himanshu Yadav, Anurag Jain
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 22
Year of Publication: 2013
Authors: Rohina Ansari, Himanshu Yadav, Anurag Jain
10.5120/11713-7337

Rohina Ansari, Himanshu Yadav, Anurag Jain . A Survey on Blurred Images with Restoration and Transformation Techniques. International Journal of Computer Applications. 68, 22 ( April 2013), 29-33. DOI=10.5120/11713-7337

@article{ 10.5120/11713-7337,
author = { Rohina Ansari, Himanshu Yadav, Anurag Jain },
title = { A Survey on Blurred Images with Restoration and Transformation Techniques },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 22 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number22/11713-7337/ },
doi = { 10.5120/11713-7337 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:37.953529+05:30
%A Rohina Ansari
%A Himanshu Yadav
%A Anurag Jain
%T A Survey on Blurred Images with Restoration and Transformation Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 22
%P 29-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In modern science and technology, digital images gaining popularity due to increasing requirement in many fields like medical research, astronomy, remote sensing, graphical use etc. Therefore, the quality of images matters in such fields. There are many ways by which the quality of images can be improved. Image restoration is one of the emerging methodologies among various existing techniques. Image restoration is the process of simply obtaining an estimated original image from the blurred, degraded or corrupted image. The primary goal of the image restoration is the original image is recovered from degraded or blurred image . This paper contains the review of many different schemes of image restoration that are based on blind and non-blind de-convolution algorithm using transformation techniques.

References
  1. Syaidatul Akma Mohd Zuki, Ihsan Mohd Yassin, "A review of image processing technique in particle mixing analysis", IEEE 2012, pp 466-469.
  2. M. Ravudu, V. Jain, and M. M. R. Kunda, "Review of image processing techniques for automatic detection of eye diseases ", IEEE 2012, pp 320-325.
  3. You-Yi Zheng, Ji-Lai Rao and Lei Wu, "Edge detection methods in digital image processing", IEEE 2010, pp 417-473.
  4. BI Xiao-jun, WANG Ting," Adaptive Blind Image Restoration Algorithm of Degraded Image", IEEE 2008.
  5. Jinlian Zhuang and Youshen Xia "A Two-Dimensional Iterative Algorithm for Blind Image Restoration based on An L1 Regularization Approach", 2010 3rd International Congress on Image and Signal Processing (CISP2010), pp. 51 – 55, 2010.
  6. S. Ramya, T. Mercy Christial "Restoration of blurred images using Blind Deconvolution Algorithm", 2011 International Conference on Emerging Trends in Electrical and Computer Technology (ICETECT), pp. 496 – 499, March 2011.
  7. Sun qi1, Hongzhi Wang 2, Lu wei3," An iterative blind deconvolution image restoration algorithm based on adaptive selection of regularization parameter",IEEE 2009.
  8. Anna Tonazzini, Ivan Gerace, and Francesca Martinelli," Multichannel Blind Separation and Deconvolution of Images for Document Analysis", IEEE 2010.
  9. Ryu Nagayasu, Naoto Hosoda, Nari Tanabe, Hideaki Matsue, Toshihiro Furukawa," Restoration Method For Degraded Images Using Two-Dimensional Block Kalman Filter With Colored Driving Source",Ieee 2011.
  10. Renting Liu Jiaya Jia," Reducing Boundary Artifacts In Image Deconvolution,"IEEE 2008.
  11. Jong-Ho Lee, Yo-Sung Ho, "High-quality non-blind image deconvolution with adaptive regularization", Elsevier 2011.
  12. Y. Y. Tang, and L. Feng, "Multi-resolution Adaptive Wavelet Edge Detection," The 2th International Conference on Multimodal Interface, January 1999, v7-v11.
  13. Y. Y. Tang, and L. Yang, "Characterization and Detection of Edges by Lipchitz Exponents and MASW Wavelet Transform," 14th International Conference on Pattern Recognition, August 1998, pp. 1572-1574.
  14. Y. Y. Tang, L. Yang and J. Liu, "Characterization of Dirac-Structure Edges with Wavelet Transform," IEEE Trans. Systems, Man and Cybernetics, Part B, February 2000, pp. 93-109.
  15. Wangli Ouyang, Rengi Zhang, Wai-Kuen K. Cham, "Fast pattern matching using orthogonal Haar transform". IEEE 2010, pp 3050-3057
  16. Dimitrios A. Karras,"Efficient medical image compression/reconstruction applying Discrete Wavelet Transform on texturally clustered regions", IEEE 2005,pp 87-91(dwt)
  17. Sunghyun Chao, Yasuyuki Matushita,Seung-Yong Lee, "Removing Non-uniform Motion Blur from images", IEEE 2007,pp 1-8.
  18. Hideyuki Imai, Masaaki Miyakoshi, "Image restoration with kernel component estimation in singular observation process", IEEE 2003, pp 186-189.
Index Terms

Computer Science
Information Sciences

Keywords

Image processing Blurred images Padding kernel Canny edge Transformation techniques

Powered by PhDFocusTM