Quality Assessment for Virtual View Image Based on Edge Difference
-
摘要: 为了降低多视视频中的传输数据量,可适当减少包含纹理图及其对应深度图的多视数量,而在自由立体视频系统的终端采用基于深度图的绘制技术,生成新的虚拟视点。由于不准确的深度图估计、遮挡及合成算法等原因,合成虚拟视的边缘会出现高频噪声。对于这种特有的失真,用一般的评价方法并不能准确反映人眼的视觉感知。该文在分析失真虚拟视与原始视像素差异基础上,对各差异像素进行分类,并分配权重,提出了一种基于视觉加权的边缘差异质量评价方法,对边缘像素施加较高权重。经多视视频序列实验证明,该文方法相比于其它评价方法,能更好地预测人类视觉对虚拟视图像的主观感知。Abstract: In order to reduce the transmission data in the multi-view video, the number of multi-views can be decreased properly which include texture images and depth maps, and the intermediate virtual views are generated based on Depth Image Based Rendering (DIBR) at terminal for rendering on 3D displays. Generally, the view synthesis increases the high frequency components on the edge due to inaccurate estimation of the depth map, occlusion and synthesis algorithms. Conventional 2D image quality metric is difficult to reflect the virtual view distortion. In this paper, quality evaluation method based on the edge difference is proposed. Based on the analysis of the pixel difference between virtual and original views, each difference pixel is classified and assigned a visual weight, and higher weights applied to the edge pixels. Experiments for multi-view video sequences prove that the results of this metric are in accordance with characteristic of human visual system.
-
Key words:
- Video image /
- Quality assessment /
- Edge difference /
- Virtual view /
- Visual weight /
- Depth Image Based Rendering (DIBR)
期刊类型引用(4)
1. 王晨,彭宗举,章联军,陈芬,陆志华. 基于偏度和结构特征的无参考虚拟视点图像质量评价. 计算机应用. 2021(S2): 226-233 . 百度学术
2. 孙彦景,杨玉芬,刘东林,施文娟. 基于内在生成机制的多尺度结构相似性图像质量评价. 电子与信息学报. 2016(01): 127-134 . 本站查看
3. 马祥,霍俊彦,任光亮,杨旭,常义林. 利用视频与深度图相关性的深度图帧内编码. 西安电子科技大学学报. 2015(03): 1-7 . 百度学术
4. 陈悦,姚剑敏,郭太良. 基于背景提取和分区修复的DIBR空洞填补方法. 电视技术. 2014(23): 34-37 . 百度学术
其他类型引用(5)
-
计量
- 文章访问数: 2622
- HTML全文浏览量: 124
- PDF下载量: 1207
- 被引次数: 9