Client-Oriented Blind Quality Metric for High Dynamic Range Stereoscopic Omnidirectional Vision Systems

Autor: Liuyan Cao, Jihao You, Yang Song, Haiyong Xu, Zhidi Jiang, Gangyi Jiang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Sensors, Vol 22, Iss 21, p 8513 (2022)
Druh dokumentu: article
ISSN: 22218513
1424-8220
95403833
DOI: 10.3390/s22218513
Popis: A high dynamic range (HDR) stereoscopic omnidirectional vision system can provide users with more realistic binocular and immersive perception, where the HDR stereoscopic omnidirectional image (HSOI) suffers distortions during its encoding and visualization, making its quality evaluation more challenging. To solve the problem, this paper proposes a client-oriented blind HSOI quality metric based on visual perception. The proposed metric mainly consists of a monocular perception module (MPM) and binocular perception module (BPM), which combine monocular/binocular, omnidirectional and HDR/tone-mapping perception. The MPM extracts features from three aspects: global color distortion, symmetric/asymmetric distortion and scene distortion. In the BPM, the binocular fusion map and binocular difference map are generated by joint image filtering. Then, brightness segmentation is performed on the binocular fusion image, and distinctive features are extracted on the segmented high/low/middle brightness regions. For the binocular difference map, natural scene statistical features are extracted by multi-coefficient derivative maps. Finally, feature screening is used to remove the redundancy between the extracted features. Experimental results on the HSOID database show that the proposed metric is generally better than the representative quality metric, and is more consistent with the subjective perception.
Databáze: Directory of Open Access Journals
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