Adaptive Resolution Upconversion for Compressed Video Using Pixel Classification

Shao, Ling (2007) Adaptive Resolution Upconversion for Compressed Video Using Pixel Classification. EURASIP Journal on Advances in Signal Processing, 2007. pp. 1-7. ISSN 1687-6172

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Official URL: http://dx.doi.org/10.1155/2007/71432

Abstract

A novel adaptive resolution upconversion algorithm that is robust to compression artifacts is proposed. This method is based on classification of local image patterns using both structure information and activity measure to explicitly distinguish pixels into content or coding artifacts. The structure information is represented by adaptive dynamic-range coding and the activity measure is the combination of local entropy and dynamic range. For each pattern class, the weighting coefficients of upscaling are optimized by a least-mean-square (LMS) training technique, which trains on the combination of the original images and the compressed downsampled versions of the original images. Experimental results show that our proposed upconversion approach outperforms other classification-based upconversion and artifact reduction techniques in concatenation.

Item Type: Article
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Depositing User: Paul Burns
Date Deposited: 15 Jun 2015 12:48
Last Modified: 12 May 2017 05:06
URI: http://nrl.northumbria.ac.uk/id/eprint/22900

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