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A Multiplierless VLSI Architecture of QR Decomposition Based 2D Wiener Filter for 1D/2D Signal Processing With High Accuracy

机译:基于QR分解的QR分解的多平台VLSI架构,用于高精度的1D / 2D信号处理的QR分解的2D Wiener滤波器

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Now-a-days real-time signal processing attracts growing interests from the researchers all over the world due to its advantageous nature in solving various hindrances that frequently occur in various significant signal processing applications. Specifically, digital images suffer from noise contamination and blurring effect which poses difficulties in extracting useful information from those images. This necessitates the removal of noises from those digital images as well as de-blurring of such images in real-time. In this article, we have proposed a low area and highly accurate VLSI architecture of 2D Wiener filter which can be applied for any1D/2D real-time signal efficiently. The applicability of inherently highly accurate Wiener filter throttles due to its computational complexities. Our focus in this article is to overcome the barrier by reducing the computational complexity using Toeplitz matrix formation and its QR decomposition. We have proposed an area efficient multiplier-less VLSI architecture for realizing 2D Wiener filter. We have exploited the concept of Givens rotation based QR decomposition and also we have utilized the CORDIC algorithm to achieve high performance of our design. We have also applied our proposed hardware in real-time audio signal and image denoising. The supremacy of our proposed design can be proved from the analysis of pictorial and also numerical results.
机译:现在,由于其在各种显着信号处理应用中经常出现的各种障碍方面,目前的实时信号处理吸引了来自世界各地的研究人员的兴趣。具体地,数字图像遭受噪声污染和模糊效果,其在从那些图像中提取有用信息时造成困难。这需要从那些数字图像中除去噪声以及实时地对这些图像的去模糊。在本文中,我们已经提出了一个低区域和高精度的VLSI架构的2D维纳滤波器,其可以有效地应用于Any1D / 2D实时信号。由于其计算复杂性,固有高度精确的维纳滤波器的适用性。我们在本文中的重点是通过使用Toeplitz矩阵形成来克服屏障及其QR分解来克服计算复杂性。我们提出了一个用于实现2D维纳滤波器的区域有效的乘法器架构。我们已经利用了基于Givens旋转的QR分解的概念,并且我们已经利用了Cordic算法来实现我们设计的高性能。我们还在实时音频信号和图像去噪中应用了我们提出的硬件。我们提出的设计的至高无上可以证明从图案的分析和数值结果。

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