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Publication Type : Conference Paper
Publisher : Procedia Computer Science, Elsevier.
Source : Procedia Computer Science, Elsevier, Volume 93, p.495-502 (2016)
Keywords : Bandpass filters, Convex optimization, De-noising, Image denoising, Image processing, noise, Norm, Optimization, PSNR, Signal denoising, Signal to noise ratio, SSIM, Wavelet denoising
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking, Electronics Communication and Instrumentation Forum (ECIF)
Department : Electronics and Communication
Year : 2016
Abstract : The major problem in digital image processing is the presence of unwanted frequencies(noise). In this paper ℓ1 trend filter is proposed as an image denoising technique. ℓ1-trend filter estimates the hidden trend in the data by formulating a convex optimization problem based on ℓ1 norm. The proposed method extends the application of ℓ1 trend filter from one dimensional signals to three dimensional color images. Here the filter is applied over the image in a cascade, initially filtering along the rows followed by filtering along the columns. This identifies the hidden image information from the noisy image resulting in a smooth or denoised image. The proposed method is compared with the wavelet denoising technique using the quality metrics Peak-Signal-to-Noise-Ratio(PSNR) and Structural Similarity Index(SSIM). © 2016 The Authors. Published by Elsevier B.V.
Cite this Research Publication : S. Selvin, Ajay, S. G., Gowri, B. G., and Dr. Soman K. P., “ℓ1 Trend Filter for Image Denoising”, in Procedia Computer Science, 2016, vol. 93, pp. 495-502.