Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/7205
Title: Adaptive Reconfigurable Architecture for Image Denoising
Authors: Hegde, K.V.
Kulkarni, V.
Harshavardhan, R.
Sumam, David S.
Issue Date: 2015
Citation: Proceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015, 2015, Vol., , pp.196-201
Abstract: In this paper, we propose an adaptive reconfigurable architecture for image denoising. First part of this paper outlines an efficient noise detection hardware for Gaussian & impulse noise detection and suitable filters for denoising. With a robust noise detection method including a novel Gaussian noise detection method, we also explore the dynamic detection of noise in an image giving adaptability to the architecture for a better quality of denoising. Proposed architecture includes a decision making unit to find out the presence of noise as well as type of the noise, based on which a suitable filter is employed during run-time. An onboard microprocessor controls the reconfiguration and dataflow. Proposed architecture is tested on Xilinx Virtex-6 FPGA with localized noise and mixed noise conditions and it gives superior performance compared to the standard filters used. High quality denoising is achieved with simple filters on a reconfigurable region utilizing smaller area and lesser hardware resources. � 2015 IEEE.
URI: https://idr.nitk.ac.in/jspui/handle/123456789/7205
Appears in Collections:2. Conference Papers

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