A Novel Approach of Image Restoration Based on Segmentation and Fuzzy Clustering
Image restoration is the process of restoring or deblurring an image which had been undergone certain degradations. In this paper, we proposed a method for image restoration based on segmentation and fuzzy clustering. This method consider the similar image pair in which there is a clear part in one image corresponding to degraded one in another. This proposed method firstly partition the image into specified segments and then use fuzzy clustering to cluster the segment based on their peak signal-to-noise ratio (PSNR) value and provide the segments that needs to restore. The performance of the system is evaluated on the basis of PSNR value. The proposed method shows higher efficiency compared to the existing methods.
Kundar D, Hatzinakos D. Blind Image Deconvolution. IEEE Signal Processing Magazine. 1996 May; 1053: 43–64p.
Banham MR, Katsaggelos AK. Digital Image Restoration. IEEE Signal Processing Magazine. 1997 Mar; 14(2): 24–41p.
Bilgen M, Hung HS. Restoration of noisy images blurred by a random point spread function. IEEE International Symposium on Circuits and Systems; 1990 May 1–3; New Orleans, LA. USA: IEEE; 1990.
Moghaddam ME. A mathematical model to estimate out of focus blur. Proceedings of the 5th International Symposium on image and Signal Processing and Analysis; 2007 Sep 27–29; Istanbul, Turkey. USA: IEEE Xplore; 2007.278–81p.
Qin FQ, Min J, Guo H. A blind image restoration based on PSF estimation. Proceedings of IEEE World Congress on Software Engineering; 2009 May 19–21; Xiamen, China. USA: IEEE; 2009.173–76p.
Srivastava R, Parthasarthy H, Gupta JRP, et al. Image Restoration from Motion Blurred Image using PDEs formalism. Proceedings of IEEE International Advance Computing Conference; 2009 Mar 6–7; Patiala, India. USA:IEEE; 2009.61–4.
Shaojie S, Qiong W, Guohui L. Image Restoration for Single Blurred Image. Proceedings of IEEE International Conference on Intelligent Computing and Intelligent Systems; 2009 Nov 20–22; Shanghai, China.USA: IEEE; 2009.491–5p.
Bhagat KR, Gour P. Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques. IJCA. 2013; 72(17): 21–6p.
Mahmoud H, Masulli F, Rovetta S. Feature-Based Medical Image Registration using Fuzzy Clustering Segmentation Approach. In: Peterson LE, Masulli F, Russo G,editors. Computational Intelligence Methods for Bioinformatics and Biostatistics Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg; 2007.
Moghaddam ME, Jamzad M. Motion blur identification in noisy images using fuzzy sets. Proceedings of the 5th IEEE International Symposium on Signal Processing and Information Technology; 2005 Dec 21; Athens, Greece. USA: IEEE; 2005. 862–66p.
Ramya S, Christial TM. Restoration of blurred images using Blind Deconvolution Algorithm. Proceedings of International Conference on Emerging Trends in Electrical and Computer Technology (ICETECT);2011 Mar 23–24; Tamil Nadu, India. USA: IEEE; 2011.496–99p.
Duan J, Meng G, Xiang S, et al. Removing out-of-focus blur from similar image pairs. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 2013 May 26–31; Vancouver,BC. USA:IEEE; 2013.1617–21p.
- There are currently no refbacks.