{"title":"A Display Method of Large Underwater Photo-Mosaics Based on Pyramid Model of Tiled Images","authors":"Nannan Liu, Xiaoming Li","doi":"10.1109/CCAI50917.2021.9447465","DOIUrl":null,"url":null,"abstract":"In deep seafloor exploration, optical imaging provides short-range, high resolution visual information. In order to obtain a wide range of detailed visual information, it is common to stitch multiple images into a photo-mosaic which could reach tens of billions of pixels in size. Due to hardware and software constraints, it is very difficult even impossible to browse and display such a large image with existing image viewers. In this paper, we propose a display method based on pyramid model and develop a super large image display system of tiled images dedicated to underwater photo-mosaics display. Before the image can be displayed, the first step is to construct and store the multi-resolution hierarchical model of tiles, in which sub-mosaics of the same size are original tiles with the highest resolution. Similar to quadtree coding, each tile is encoded based on its location in the pyramid. Then all tile data are stored in MongoDB database. Each record in MongoDB is a key-value pair structure corresponding to a specific tile, in which key is the encoding of a tile and value is the tiled image data stored in binary stream format. Image display is implemented based on graphical user interface. By mouse operation, the system can display images at different resolutions and browse different part of the image. Based on the pyramid model and key-value storage structure, there are more than 60,000 high-definition tiled images in our application. The full panorama resolution is 16.2 billion pixels, about 45GB in RAM, but only the tiles displayed in the current window need to be loaded. Hence, our system reduces the memory requirement greatly and makes image browsing more smoothly.","PeriodicalId":121785,"journal":{"name":"2021 International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer Communication and Artificial Intelligence (CCAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCAI50917.2021.9447465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In deep seafloor exploration, optical imaging provides short-range, high resolution visual information. In order to obtain a wide range of detailed visual information, it is common to stitch multiple images into a photo-mosaic which could reach tens of billions of pixels in size. Due to hardware and software constraints, it is very difficult even impossible to browse and display such a large image with existing image viewers. In this paper, we propose a display method based on pyramid model and develop a super large image display system of tiled images dedicated to underwater photo-mosaics display. Before the image can be displayed, the first step is to construct and store the multi-resolution hierarchical model of tiles, in which sub-mosaics of the same size are original tiles with the highest resolution. Similar to quadtree coding, each tile is encoded based on its location in the pyramid. Then all tile data are stored in MongoDB database. Each record in MongoDB is a key-value pair structure corresponding to a specific tile, in which key is the encoding of a tile and value is the tiled image data stored in binary stream format. Image display is implemented based on graphical user interface. By mouse operation, the system can display images at different resolutions and browse different part of the image. Based on the pyramid model and key-value storage structure, there are more than 60,000 high-definition tiled images in our application. The full panorama resolution is 16.2 billion pixels, about 45GB in RAM, but only the tiles displayed in the current window need to be loaded. Hence, our system reduces the memory requirement greatly and makes image browsing more smoothly.