Yuejianan Gu, Y. Piao, Ying Wang, Miaomiao Xu, Che Liu
{"title":"基于改进双侧滤波的积分成像深度图恢复方法","authors":"Yuejianan Gu, Y. Piao, Ying Wang, Miaomiao Xu, Che Liu","doi":"10.1109/ICCSNT50940.2020.9305006","DOIUrl":null,"url":null,"abstract":"In order to use a depth camera to simplify the acquisition process of integral imaging, this paper proposes a depth map restoration algorithm combining pixel filling and improved joint bilateral filtering(DIJBF). The depth image collected by the depth camera has the problems of background noise and holes in the foreground and background of the object. Firstly, the background filling method or the neighborhood value filling method is adopted to complete the preliminary restoration of the large edge void area according to the situation, and then combined with the improved joint bilateral filtering algorithm that adds the depth image depth value similarity factor to optimize the secondary restoration of the preliminary restoration depth map. After the depth image is restored and optimized, the contour of the three-dimensional object is clear and the edge is smooth. Combined with the color image, a high-quality elemental image array can be subsequently generated for the integral imaging display system.","PeriodicalId":6794,"journal":{"name":"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"17 1","pages":"37-40"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Depth Map Restoration Method based on Improved Bilateral Filtering for Integral Imaging\",\"authors\":\"Yuejianan Gu, Y. Piao, Ying Wang, Miaomiao Xu, Che Liu\",\"doi\":\"10.1109/ICCSNT50940.2020.9305006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to use a depth camera to simplify the acquisition process of integral imaging, this paper proposes a depth map restoration algorithm combining pixel filling and improved joint bilateral filtering(DIJBF). The depth image collected by the depth camera has the problems of background noise and holes in the foreground and background of the object. Firstly, the background filling method or the neighborhood value filling method is adopted to complete the preliminary restoration of the large edge void area according to the situation, and then combined with the improved joint bilateral filtering algorithm that adds the depth image depth value similarity factor to optimize the secondary restoration of the preliminary restoration depth map. After the depth image is restored and optimized, the contour of the three-dimensional object is clear and the edge is smooth. Combined with the color image, a high-quality elemental image array can be subsequently generated for the integral imaging display system.\",\"PeriodicalId\":6794,\"journal\":{\"name\":\"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)\",\"volume\":\"17 1\",\"pages\":\"37-40\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSNT50940.2020.9305006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSNT50940.2020.9305006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Depth Map Restoration Method based on Improved Bilateral Filtering for Integral Imaging
In order to use a depth camera to simplify the acquisition process of integral imaging, this paper proposes a depth map restoration algorithm combining pixel filling and improved joint bilateral filtering(DIJBF). The depth image collected by the depth camera has the problems of background noise and holes in the foreground and background of the object. Firstly, the background filling method or the neighborhood value filling method is adopted to complete the preliminary restoration of the large edge void area according to the situation, and then combined with the improved joint bilateral filtering algorithm that adds the depth image depth value similarity factor to optimize the secondary restoration of the preliminary restoration depth map. After the depth image is restored and optimized, the contour of the three-dimensional object is clear and the edge is smooth. Combined with the color image, a high-quality elemental image array can be subsequently generated for the integral imaging display system.