Publication Type:

Conference Paper

Source:

Procedia Computer Science, Elsevier, Volume 93, p.495-502 (2016)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84985947328&partnerID=40&md5=10a9577f2182931ebef5bc76e9991ac0

Keywords:

Bandpass filters, Convex optimization, De-noising, Image denoising, Image processing, noise, Norm, Optimization, PSNR, Signal denoising, Signal to noise ratio, SSIM, Wavelet denoising

Abstract:

<p>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.</p>

Notes:

cited By 0; Conference of 6th International Conference On Advances In Computing and Communications, ICACC 2016 ; Conference Date: 6 September 2016 Through 8 September 2016; Conference Code:131418

Cite this Research Publication

S. Selvin, Ajay, S. G., Gowri, B. G., and Soman, K. P., “ℓ1 Trend Filter for Image Denoising”, in Procedia Computer Science, 2016, vol. 93, pp. 495-502.

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