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Open Access A Referenceless Image Quality Assessment Based on BSIF, CLBP, LPQ, and LCP Texture Descriptors

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In the last decades, many researchers have developed algorithms that estimate the quality of a visual content (videos or images). Among them, one recent trend is the use of texture descriptors. In this paper, we investigate the suitability of using Binarized Statistical Image Features (BSIF), the Local Configuration Pattern (LCP), the Complete Local Binary Pattern (CLBP), and the Local Phase Quantization (LPQ) descriptors to design a referenceless image quality assessment (RIQA) method. These descriptors have been successfully used in computer vision applications, but their use in image quality assessment has not yet been thoroughly investigated. With this goal, we use a framework that extracts the statistics of these descriptors and maps them into quality scores using a regression approach. Results show that many of the descriptors achieve a good accuracy performance, outperforming other state-of-the-art RIQA methods. The framework is simple and reliable.
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Keywords: features; lbp; quality metrics; quality of experience; texture

Document Type: Research Article

Publication date: January 13, 2019

This article was made available online on January 13, 2019 as a Fast Track article with title: "A referenceless image quality assessment based on BSIF, CLBP, LPQ, and LCP texture descriptors".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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