Browsing by Author "Hegde, K.V."

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    Adaptive Reconfigurable Architecture for Image Denoising
    (2015) Hegde, K.V.; Kulkarni, V.; Harshavardhan, R.; Sumam, David S.
    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.
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    Adaptive Reconfigurable Architecture for Image Denoising
    (Institute of Electrical and Electronics Engineers Inc., 2015) Hegde, K.V.; Kulkarni, V.; Harshavardhan, R.; Sumam David, S.
    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.