Novel Approaches for Image Denoising using Augmented Algorithms
SK. Faiz Ahmed1, K. Ramesh Reddy2
1SK. Faiz Ahmed, Research Scholar, Department of Computer Science & Engineering, Rayala Seema University Government, Kurnool (A.P), India.
2Dr. K. Ramesh Reddy, Assistant Professor, Department of Computer Science, Vikrama Simhapuri University, Government, Nellore (A.P), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 77-81 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3372048619/19©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: Images Recurrently Received in an Impaired Quality due to indigent image capturing, scanning and transmitting devices. This demands the image denoising. In this paper, we proposed two novel approaches for image denoising. The first one based on geometrical pixel location computes the details of the processed image with modifications in encoding and decoding process. The input image filtered and the selected geometric positions were encoded. During the image decoding process, the original geometric locations were observed for quality of denoising. The computed parameters are Peak Signal to Noise Ratio (PSNR), Structural Similarity index (SSIM), Mean Square Error (MSE) and computation time. The second approach based on an improved genetic algorithm (GA). The existing techniques mostly involve non-neighbourhood creates suspicion in the calculation of the contents of an image .These redundancies further cause the complications and able to be abused to evacuate the commotion in the image. Thus, our proposed improved GA approach based on the scheme called picture denoising component with enhanced hereditary calculation. The results obtained shows the superiority of the proposed two approaches in image denoising.
Keyword: Image Denoising, Genetic Algorithm, Geometric Pixel Location, Pixel Encoder, PSNR, SSIM.
Scope of the Article: Image Processing