Denoising: A Dual Domain Method
Aravind B N1, K V Suresh2
1Aravind B N*, Department of Electronics and Communication Engineering, Rajeev Institute of Technology, Hassan, India.
2K. V. Suresh, Department of Electronics and Communication Engineering, Siddaganga Institute of Technology, Tumkur, India.
Manuscript received on October 11, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 1588-1592 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4555119119/2019©BEIESP | DOI: 10.35940/ijitee.A4555.119119
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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: Image has an important role to play in our daily life. It has its applications from simple documentation to complicated surveillance and medical applications. In the area of image processing, denoising is one among the most studied areas. Many a times the captured image will be degraded. This can happen at the time of acquisition and/or transmission. Noise is one such degrading agent. The presence of noise will affect the performance of the applications like segmentation, recognition, object detection and medical as well as general applications. Hence denoising is a prerequisite in these applications. The proposed method utilizes both transform and spatial domains. Shrinkage technique is applied in wavelet domain and in spatial domain, non-local means is used. Simulation is conducted on standard test images. The tabulated results shows that, the proposed method performs comparatively better.
Keywords: Dual Domain, Image Denoising, Nonlocal Means, Shrinkage.
Scope of the Article: Communication