A Multiplierless VLSI Architecture of QR Decomposition Based 2D Wiener Filter for 1D/2D Signal Processing With High Accuracy
Anirban Chakraborty, Ayan Banerjee · 2018
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.