| 利用边缘相似度的光场图像质量评价 |
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| 引用本文： | 田钰,曾焕强,邢露,符颖,蔡灿辉.利用边缘相似度的光场图像质量评价[J].信号处理,2018,34(10):1197-1202. |
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| 作者姓名： | 田钰 曾焕强 邢露 符颖 蔡灿辉 |
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| 作者单位： | 华侨大学信息科学与工程学院,厦门市移动多媒体通信重点实验室 |
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| 基金项目： | 国家自然科学基金项目（61401167）;福建省自然科学基金项目（2016J01308, 2017J05103）;泉州市高层次人才创新创业项目（2017G027）;华侨大学中青年教师科研提升资助计划（ZQN-YX403);华侨大学高层次人才资助项目（16BS709, 14BS201, 14BS204）
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| 摘 要： | 近年来，随着虚拟现实（Virtual Reality，VR）和增强现实（Augment Reality，AR）技术发展和普及，光场图像引起了学术界和工业界的广泛关注。然而，在光场采集和图像压缩、存储、传输和渲染的过程中，不可避免会引入各类失真从而导致光场图像质量出现劣化。因此，如何根据人眼视觉特性来准确高效地评价光场图像质量成为急需解决的问题。考虑到光场图像复杂的结构特性，本文意在利用边缘相似度来构建适用于光场图像质量客观评估的数学模型。首先, 利用梯度和Gabor滤波器分别提取光场图像的空域和频域相似度，进而进行融合得到边缘相似度图，接着对边缘相似度图采用基于频域边缘强度的池化策略进行权重计算得到最终的客观评估分数。实验结果显示，与现有的图像质量评价方法相比，本文所提算法能够更好地反映出人类视觉系统对光场图像的主观感知特性。
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| 关 键 词： | 光场图像 图像质量评价 人类视觉系统 边缘相似度 |
| 收稿时间： | 2018-05-03 |
Light Field Image Quality Assessment Using Edge Similarity |
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| Affiliation: | School of Information Science and Engineering, Huaqiao University, Xiamen Key Laboratory of ?Mobile Multimedia Communications |
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| Abstract: | With the development and popularization of virtual reality and augment reality technology in recent years, light field image has been received extensive attentions in academia and industry. However, in the stages of acquisition, compression, storage, transmission and display, light field image are inevitably suffered from a wide various distortions, leading to image quality reduction. Therefore, it is very essential to evaluate the quality of light field image based on the characteristics of human visual system. Considering the structural complexity of light field image, we intend to use edge similarity to construct a mathematical model suitable for the objective assessment of light field image quality. Proposed approach utilizes the gradient and Gabor filter to extract the spatial and frequency edge similarity, and then fuses them together to obtain the edge similarity map, followed by a pooling strategy using frequency edge strength to compute the quality score. Experimental results show that the proposed algorithm is able to better reflect the human perception on light field image, compared with multiple state-of-the-art image quality assessment methods. |
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