Objective Quality Assessment of Lenslet Light Field Image Based on Focus Stack

Autor: Ping An, Xinpeng Huang, Liquan Shen, Bin Wang, Chunli Meng, Chao Yang
Rok vydání: 2022
Předmět:
Zdroj: IEEE Transactions on Multimedia. 24:3193-3207
ISSN: 1941-0077
1520-9210
DOI: 10.1109/tmm.2021.3096071
Popis: The huge amount of complex scene information recorded by light field imaging has the prospect of immersive media applications. Compression and reconstruction algorithms are crucial for the transmission, storage, and display of such massive data. Most of the existing quality evaluation indexes do not take an effective account of light field characteristics. To accurately evaluate the distortions caused by compression and reconstruction algorithms, it is necessary to construct an image evaluation index that reflects the angular-spatial characteristic of the light field. This work proposes a full reference light field image quality evaluation index, which attempts to extract less information from the focus stack to accurately evaluate the entire light field quality. The proposed framework includes three specific steps. Firstly, we construct a key refocused images extraction framework by the maximal spatial information contrast and the minimal angular information variation. Specifically, the gradient and phase congruency operators are used in the extraction framework. Secondly, a novel light field quality evaluation index is built based on the angular-spatial characteristic of the key refocused images. In detail, the features used in the key refocused images extraction framework and the chrominance feature are combined to construct the union feature. Then the similarity of the union feature is pooled by the relevant visual saliency map to get the predicted score. Finally, the overall quality of the light field is measured by applying the proposed index to the key refocused images. The high efficiency and precision of the proposed method are shown by extensive comparison experiments.
Databáze: OpenAIRE
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