An Efficient Image Downsampling Technique Using Genetic Algorithm and Digital Curvelet Transform
N. Jagadeesan
N. Jagadeesan, B.E Degree, Department of Electronics and Communication Engineering, Madras University, Chennai (Tamil Nadu), India.
Manuscript received on 18 August 2019 | Revised Manuscript received on 29 August 2019 | Manuscript Published on 06 September 2019 | PP: 1000-1007 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11910886S19/19©BEIESP | DOI: 10.35940/ijeat.F1191.0886S19
Open Access | Editorial and Publishing 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: Propelled pictures are used everywhere and are definitely not hard to manage and change in view of the availability of various picture getting ready and adjusting programming. Repeat the image to a lesser extent and change the look of the image. This can be useful at times when the original version of the original will give you a slim version of the film. There are several methods of image downsampling. This sheet uses performance capabilities for a collage based on digital curve transfers and generic algorithms. Genetic Algorithm (GA) is attached by the Digital Curvelet Transform (DCT). Originally DCT The length of the map decreases by using. Using this reduced map, gateways and entry worth are coordinated by the utilization of hereditary estimation. From the appraisal of results, it will when all is said in done be picked that the proposed method is quick and exact.
Keywords: Image Downsampling, Genetic Algorithm (GA), Digital Curvelet Transform (DCT), Motion Filter, Soft Thresholding.
Scope of the Article: Digital Clone or Simulation