VLSI Implementation of a Real-time Modified Decision-based Algorithm for Impulse Noise Removal

P. K. Sanki, Vasudeva Bevara, Medarametla Deepthi Supriya, Devireddy Vignesh, Peram Bhanu Sai Harshath, Siavya Kuchina
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引用次数: 1

Abstract

In this paper, a Real-Time Impulse Noise Removal (RTINR) algorithm and its hardware architecture are proposed for denoising images corrupted with fixed valued impulse noise. A decision-based algorithm is modified in the proposed RTINR algorithm where the corrupted pixel is first detected & is restored with median or previous pixel value depending on the number of corrupted pixels in the image. The proposed RTINR architecture has been designed to reduce the hardware complexity as it requires 21 comparators, 4 adders, and 2 line buffers which in turn improve the execution time. The proposed architecture results better in qualitative and quantitative performance in comparison to different denoising schemes while evaluated based on PSNR, IEF, MSE, EKI, SSIM,& FOM. The proposed architecture has been simulated using the VIRTEX7 FPGA device and the reported maximum post place& route frequency is 360.88 MHz. The proposed RTINR architecture is capable of denoising images of size 512 × 512 at a frame rate of 686. The architecture has also been synthesized using UMC 90 nm technology where 103 mW power is consumed at a clock frequency of 100 MHz with a gate count of 2.3K (NAND2) including two memory buffers.
一种基于决策的实时改进脉冲噪声去除算法的VLSI实现
本文提出了一种实时脉冲噪声去除(RTINR)算法及其硬件结构,用于去除固定值脉冲噪声损坏的图像。在提出的RTINR算法中,改进了基于决策的算法,首先检测损坏的像素,并根据图像中损坏的像素数量使用中值或先前的像素值进行恢复。提议的RTINR架构旨在降低硬件复杂性,因为它需要21个比较器、4个加法器和2个行缓冲区,这反过来又提高了执行时间。在基于PSNR、IEF、MSE、EKI、SSIM和FOM进行评估的基础上,与不同的去噪方案相比,所提出的架构在定性和定量性能上都有更好的表现。采用VIRTEX7 FPGA器件对所提出的体系结构进行了仿真,报告的最大post放置和路由频率为360.88 MHz。所提出的RTINR架构能够以686帧速率对大小为512 × 512的图像进行去噪。该架构也采用联华电子90纳米技术合成,在时钟频率为100 MHz时消耗103 mW功率,门数为2.3K (NAND2),包括两个存储缓冲区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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