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2017 年度 実施状況報告書

Modeling the Perceptual Underpinnings for Quality Assessment of Restored Textures

研究課題

研究課題/領域番号 17K00232
研究機関静岡大学

研究代表者

Chandler Damon  静岡大学, 工学部, 准教授 (70765495)

研究分担者 大橋 剛介  静岡大学, 工学部, 教授 (80293603)
研究期間 (年度) 2017-04-01 – 2020-03-31
キーワードquality assessment / restoration / enhancement / compression / visual perception
研究実績の概要

The objective of this research project is to investigate the perceptual foundations of restored textures, to research and develop associated computational models and QA algorithms for restoration applications. In Year 1, the objective was to create a restored-image database containing quality scores for degraded textures and various restored versions of those textures. This database has been created.
In particular, the images were acquired, the textures were identified and segmented, and restorative patterns were synthesized. The restorative patterns were then added to HEVC-distorted versions of images to obtain two types of data relating to quality: (1) contrast thresholds for detecting the restorative patterns, and (2) optimal contrast scaling factors and quality improvement ratings. These data will provide important insights into how the human visual system judges texture quality.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

The research is largely on-schedule. Our main objective was to create the restored-image database, which includes not only the images and textures, but also the optimal scaling factors and the associated quality scores. In the original proposal, we did not suggest measuring the contrast detection thresholds. However, in order to model/predict the optimal scaling factors, a first step is to measure the visibility of the restorative patterns. Thus, we also measured the contrast detection thresholds. This decision to explore the visibility aspect limited the number of restorative pattern types that we were able to test. However, we are currently testing other types of restorative patterns both in terms of quality and detection thresholds, which will ultimately lead to more and better data.

今後の研究の推進方策

We have the added task of measuring both optimal scaling factors and contrast detection thresholds for the other types of restorative patterns. The advantage, however, is that we expect the contrast detection thresholds to be an important factor in modeling the visual impact of the restorative patterns. As stated in the original proposal, Year 2 will focus on model development. We have currently begun to develop such models, beginning with an investigation of the relationship between the visibility and optimal scaling factors. We believe that a perceptual model which uses basic similarity measures between the original vs. restored textures, will be able to quantify both the visibility and amount of quality change. One new M.S. student will focus exclusively on this modeling effort.

次年度使用額が生じた理由

The ordering of machines and desks was postponed due to additional students joining our research lab mid-year or later. For this reason, we have requested the remaining funds from Year 1 to be transferred to Year 2. Other students will contribute to this project by exploring other related perceptual aspects (e.g., other forms of distortion such as blur caused by resizing, and other texture-analysis measures such as texture regularity). These transferred funds will be used to pay for workstations/desks for these students. Some of the funds may be used for dissemination of the contrast-threshold study at a conference (currently under review).

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公開日: 2018-12-17  

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