Temat: no reference metric - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: The Design of an Objective Metric and Construction of a Prototype System for Monitoring Perceived Quality (QoE) of Video Sequences
Autorzy:: Janowski, L.
Leszczuk, M.
Papir, Z.
Romaniak, P.
Powiązania:: https://bibliotekanauki.pl/articles/307891.pdf
Data publikacji:: 2011
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: mean opinion score
no reference metric
objective metric
quality of experience
video artefacts
Opis:: The paper presents different no reference (NR) objective metrics addressing the most important artefacts for raw (source) video sequences (noise, blur, exposure) and those introduced by compression (blocking, flickering) which can be used for assessing quality of experience. The validity of all metrics was verified under subjective tests.
Źródło:: Journal of Telecommunications and Information Technology; 2011, 3; 87-94
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: No-reference quality metric for high dynamic range imaging system based on curvature analysis in tensor domain
Autorzy:: Jiang, Gangyi
Yu, Jiaowen
Yu, Mei
Song, Yang
Peng, Zongju
Chen, Fen
Powiązania:: https://bibliotekanauki.pl/articles/173642.pdf
Data publikacji:: 2019
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:: high dynamic range image
no-reference quality metric
tensor domain
curvature analysis
quality-related label feature matrix
Opis:: High dynamic range imaging systems can offer a more complete representation of scene, aiming to capture all brightness information of a visible range of scene, even in extreme lighting conditions.This paper proposes a no-reference quality metric for high dynamic range image (HDRI), in which a combination of tensor decomposition and curvature analysis is used to construct an efficient featureset that is sensitive to degradation levels of patches in HDRIs. Tensor decomposition maintains the majority of color information of an HDRI, and the geometric structure information of the HDRI is then extracted by a curvature analysis. A quality-related label feature matrix is subsequently defined and obtained by using a feature set and a sparse dictionary with quality-related labels. Then, the multi-dimensional local feature set of the HDRI is determined from the quality-related label feature matrix. Finally, the local feature set and other global feature set are pooled to predict the quality of the HDRI. The prediction performance of the proposed metric is verified by three public test databases, and the experimental results indicate that both its Pearson linear correlation coefficientand Spearman rank-order correlation coefficient are better than those of other no-reference metrics.The proposed metric produces statistically better assessment results, implying a higher consistency with human visual perception.
Źródło:: Optica Applicata; 2019, 49, 4; 527-543
0078-5466
1899-7015
Pojawia się w:: Optica Applicata
Dostawca treści:: Biblioteka Nauki

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