Analyze the Performance of Image Compression Techniques using Hybrid and Swarm Optimization Methods
Roopesh Kumar Kurmi1, Harendra Singh2
1Roopesh Kumar Kurmi, M.Tech Scholar, Department of Computer Science and Engineering, Lakshmi Narain College of Technology Excellence (LNCTE), Bhopal (M.P), India.
2Harendra Singh, Assistant Professor, Department of Computer Science and Engineering, Lakshmi Narain College of Technology Excellence (LNCTE), Bhopal (M.P), India.
Manuscript received on 02 November 2017 | Revised Manuscript received on 21 November 2017 | Manuscript Published on 30 December 2017 | PP: 19-22 | Volume-7 Issue-2, November 2017 | Retrieval Number: B2475117217/2017©BEIESP
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© 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: Every day, a massive amount of information is stored, processed, and transmitted digitally. The primary goal of image compression is to minimize the number of bits required to represent the original images by reducing the redundancy in images, while still meeting the User defined quality requirements. Uncompressed images normally require a large amount of storage capacity and transmission bandwidth. In this paper we proposed a hybrid image compression technique for the image which is better in the terms of result by measuring performance evaluation parameters to increase the value of PSNR; our empirical results study shows that hybrid methods are better than existing techniques.
Keyword: Discrete Wavelet Transform (DWT), discrete Cosign Transform (DCT), PSNR, RGB, HVS, Image Compression
Scope of the Article: Discrete Wavelet Transform