New Cepstrum Based Image Restoration Algorithm for Grayscale Images
Ramteke Mamta G.1, Maitreyee Dutta2
1Mrs. Ramteke Mamta G, Computer science, and engineering NITTTR, Sector 26, Chandigarh, India.
2Dr. (Mrs.) Prof. Maitreyee Dutta. Department of Computer science and engineering NITTTR, Sector 26, Chandigarh, India.
Manuscript received on 22 August 2019. | Revised Manuscript received on 02 September 2019. | Manuscript published on 30 September 2019. | PP: 1920-1928 | Volume-8 Issue-11, September 2019. | Retrieval Number: K21320981119/2019©BEIESP | DOI: 10.35940/ijitee.K2132.0981119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. 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: Optimization is the process that relates to finding the most excellent ways for all possible solutions. From last 2-3 decades, natural algorithms play an important role in improving solutions of various problems. By comparing various meta-heuristic algorithms, researchers can make a choice to the best selection of the meta-heuristic algorithms for the proposed problem. In this particular research, we have applied New Cepstrum based technique of image restoration to find out PSF parameters of motion blurred images as a primary technique. In addition, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), BAT Algorithm and GA-BAT hybrid technique etc. are also applied to optimize the blur parameters for calculated by new cepstrum based technique for blur estimation. This aids in analyzing the performance of each algorithm on the same primary technique. The performance analysis of all four algorithms aid in making the decision on the best meta-heuristic algorithm of the cepstrum based technique and to identify the preciseness of the motion blur. All four methods are applied to the same set of images. The algorithm is tested and compared using grayscale images and the benchmarking freely available online datasets, respectively.
Keywords: Image Restoration, Genetic Algorithm, Parameter Estimation, Cepstrum.
Scope of the Article: Image Processing and Pattern Recognition