DEPTH ENHANCEMENT WITH IMPROVED EXEMPLAR-BASED INPAINTING AND JOINT TRILATERAL GUIDED FILTERING

被引：0

作者：

Zhang, Liang ^{[1
]}

Shen, Peiyi ^{[1
]}

Zhang, Shu'e ^{[1
]}

Song, Juan ^{[1
]}

Zhu, Guangming ^{[1
]}

机构：

[1] Xidian Univ, Sch Software, Xian, Peoples R China

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2016年

关键词：

depth enhancement; exemplar-based inpainting; joint trilateral guided filter;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Heavy noises and large amounts of holes exist in depth images captured by sensors, such as Kinect, which would severely hinder the application of depth information. In this paper, a novel depth enhancement algorithm with improved exemplar-based inpainting and joint trilateral guided filtering is proposed. The improved examplar-based inpainting method is applied to fill the holes in the depth images, in which the level set distance component is introduced in the priority evaluation function. Then a joint trilateral guided filter is adopted to denoise and smooth the inpainted results. Experimental results reveal that the proposed algorithm can achieve better enhancement results compared with the existing methods in terms of subjective and objective quality measurements.

引用

页码：4102 / 4106

页数：5