Objective Quality Assessment of Lenslet Light Field Image Based on Focus Stack
Objective Quality Assessment of Lenslet Light Field Image Based on Focus Stack
复制标题
基于焦点堆栈的小透镜光场图像客观质量评估
DOI：
10.1109/tmm.2021.3096071
复制
发表时间：
2021-07-13
影响因子：
7.3
通讯作者：
Wang, Bin
中科院分区：
文献类型：
--
作者：
Meng, Chunli;An, Ping;Wang, Bin
光场成像记录的大量复杂场景信息具有沉浸式媒体应用的潜力。压缩和重建算法对于此类大量数据的传输，存储和显示至关重要。大多数现有的质量评估指数无法有效地说明光场特征。为了准确评估由压缩和重建算法引起的扭曲，有必要构建一个反映光场角空间特征的图像评估指数。这项工作提出了一个全参考光场图像质量评估指数，该指数试图从焦点堆栈中提取更少的信息，以准确评估整个光场质量。提出的框架包括三个特定步骤。首先，我们通过最大空间信息对比度和最小角度信息变化来构建一个关键的重新聚焦图像提取框架。具体而言，在提取框架中使用了梯度和相位一致性运算符。其次，新型的光场质量评估指数是基于关键重新聚焦图像的角空间特征而构建的。详细说明，关键重新聚焦图像提取框架和色彩功能中使用的功能合并以构建联合功能。第三，联合特征的相似性由相关的视觉显着图汇总，以获得预测的分数。最后，通过将提出的索引应用于关键重新聚焦图像来衡量光场的整体质量。通过广泛的比较实验显示了提出方法的高效率和精度。
The large amount of complex scene information recorded by light field imaging has the potential for 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 effectively account for 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 characteristics of the light field. This work proposes a full-reference light field image quality evaluation index that attempts to extract less information from the focus stack to accurately evaluate the entire light field quality. The proposed framework includes three specific steps. First, we construct a key refocused image 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. Second, a novel light field quality evaluation index is built based on the angular-spatial characteristics of the key refocused images. In detail, the features used in the key refocused image extraction framework and the chrominance feature are combined to construct the union feature. Third, the similarity of the union feature is pooled by the relevant visual saliency map to obtain 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.