Modified Landweber Algorithm for Deblur and Denoise Images
Fagun Vankawala1, Amit Ganatra2
1Fagun Vankawala, U & P U. Patel, Department of Computer Engineering, Chandubhai S Patel Institute of Technology, Charusat, Changa, Ta-Petlad, Di-Anand, India.
2Amit Ganatra, U & P U. Patel, Department of Computer Engineering, Chandubhai S Patel Institute of Technology, Charusat, Changa, Ta-Petlad, Di-Anand, India.
Manuscript received on December 16, 2016 . | Revised Manuscript received on December 29, 2016 . | Manuscript published on January 05, 2016 . | PP: 79-82 | Volume-5 Issue-6, January 2016 . | Retrieval Number: F2783015616/2016©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: In this paper, we introduced modified algorithm based on traditional Landweber deblurring algorithm for reducing amount of blur and noise from satellite images. Blur image is general issue in image processing and it is hard to avoid. Image enhancement in terms of deblurring and denoising are necessary to reduce blur amount as well as noise from the image. There are few deblurring algorithms exist to deblur an image. However, if noise is present, they perform poorly. By using proposed algorithm, we get better results in terms of PSNR, execution time and complexity with blurry as well as noisy images.
Keywords: Image Deblurring, Image Denoising, Convolution, Point Spread Function (PSF), Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE).