A Study on Image Restoration and Deconvolution Techniques
Keywords:
Bayesian estimation, blind image deconvolution, Maximum A Posteriori (MAP) estimation, L1-Regularization, Iterative Distribution Reweighting (IDR)Abstract
Image restoration is the operation of taking a corrupted/noisy image and estimating the clean original image. Corruption may come in many forms such as motion blur, noise and camera misfocus. Deconvolution is an example of image restoration method. The deconvolution tries to invert the blurring of an image that is modeled by the convolution g = f*h+n. Blind deconvolution tries to do this without knowledge of the point spread function h that blurred the image. In this paper, different methods for image restoration viz. Deterministic Filter, Bayesian Estimation and iterative distribution reweighting (IDR) are discussed in detail
References
[1] Chao Wang, Lifeng Sun, Peng Cui, Zhang, Yang, “Analyzing Image Deblurring Through Three Paradigms”, IEEE Transactions on Image Processing, Vol 21 No.1,2012
[2] Mariana S.C. Almeida and Luis B.Almeida, “Blind and Semi-Blind Deblurring of Natural Images”, IEEE Transactions on Image Processing, Vol 19 No.1,2010
[3] Taeg Sang Cho, C. Lawrence Zitnick, Neel Joshi, Sing Bing Kang, Richard Szeliski, and William T. Freeman, “Image Restoration by Matching Gradient Distributions”, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 34, No. 4, April 2012
[4] Charu Khare, Kapil Kumar Nagwanshi, “Implementation and Analysis of Image Restoration Techniques”, International Journal of Computer Trends and Technology,May to June Issue 2011
[5] Mark R.Banham and Aggelos K.Katsaggelos, “Digital Image Restoration”, IEEE Signal Processing Magazine, 1997
[6] Anat Levin,Yair Weiss,Fredo Durand & William T.Freeman , “Understanding Blind Deconvolution Algorithms”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 33 No.1,2011
[7] Leah Bar,Nir Sochen and Nahum Kiryati, “Semi Blind Restoration via Mumford-Shah Regularization”, IEEE Transactions on Image Processing, Vol 15 No.2,2006
[8] Jian Feng Cai,Hui Ji,Zuowei Shen, “Framelet Based Blind Motion Deblurring from a single image”, IEEE Transactions on Image Processing, Vol 21 No.1,2011
[9] O. Milukova, V. Kober, V. Karnaukhov, and I. A. Ovseyevich, “Restoration of Blurred Images with Conditional Total Variation Method”, ISSN 1054_6618, Pattern Recognition and Image Analysis, Vol. 20, No. 2, 2010.
[10] Laura B. Montefusco and Damiana Lazzaro, “An Iterative L1-Based Image Restoration Algorithm With an Adaptive Parameter Estimation”, IEEE Transactions on Image Processing, Vol 21 No.4,2012
[11] Wangmeng Zuo and Zhouchen Lin ,”A Generalized Accelerated Proximal Gradient Approach for Total-Variation-Based Image Restoration”, IEEE Transactions on Image Processing, Vol 20 No.10,2011
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
