VLSI Architecture of Decision Based Adaptive Denoising Filter for removing salt & pepper noise Vasudeva Bevara, Bevara Srinu, Pradyut Kumar Sanki Ecs Transactions, 2022 A new Decision Based Adaptive Denoising Filter (DBADF) algorithm & hardware architecture are proposed for restoring the digital image that is highly corrupted with impulse noise. The proposed DBADF detects only the corrupted pixels and that pixel is restored by the noise-free median value or previous value based upon the noise density in the image. The proposed DBADF uses a window initially and adaptively goes up to window based on the noise corruption more than 50% by impulse noise in the current processing window. The proposed architecture was found to exhibit better visual qualitative and quantitative evaluation based on PSNR, IEF, EKI, SSIM, FOM, and error rate. The DBAMF architecture also preserves the original information of digital image with a high density of salt & pepper noise, when compared to many standard conventional algorithms. The proposed architecture has been simulated using the VIRTEX7 FPGA device and the reported maximum post place and route frequency are 149.995MHz and the dynamic power consumption is 179mW.
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A novel hardware architecture of Decision Based Adaptive Denoising Algorithm for removing salt & pepper noise V BEVARA, PK Sanki, S Bevara SGS-Engineering & Sciences 1 (01) , 2021 2021
A QoS Enhancement in Hybrid Wireless Networks using QOD Routing Protocol BS Karri Manjula International Journal of Science & Engineering Development Research 1 (11 … , 2016 2016
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