{"title":"用于火星地貌研究的背景相机(CTX)图像拼接新方法","authors":"A. Chavan, S. Sarkar, Adarsh Thakkar, S. Bhandari","doi":"10.4236/ojg.2021.118020","DOIUrl":null,"url":null,"abstract":"Various spacecraft and satellites from the world’s best space agencies are exploring Mars since 1970, constantly with great ability to capture the maximum amount of dataset for a better understanding of the red planet. In this paper, we propose a new method for making a mosaic of Mars Reconnaissance Orbiter (MRO) spacecraft payload Context Camera (CTX) images. In this procedure, we used ERDAS Imagine for image rectification and mosaicking as a tool for image processing, which is a new and unique method of generating a mosaic of thousands of CTX images to visualize the large-scale areas. The output product will be applicable for mapping of Martian geomorphological features, 2D mapping of the linear feature with high resolution, crater counting, and morphometric analysis to a certain extent.","PeriodicalId":63246,"journal":{"name":"地质学期刊(英文)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A New Method of Mosaicking Context Camera (CTX) Images for the Geomorphological Study of Martian Landscape\",\"authors\":\"A. Chavan, S. Sarkar, Adarsh Thakkar, S. Bhandari\",\"doi\":\"10.4236/ojg.2021.118020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various spacecraft and satellites from the world’s best space agencies are exploring Mars since 1970, constantly with great ability to capture the maximum amount of dataset for a better understanding of the red planet. In this paper, we propose a new method for making a mosaic of Mars Reconnaissance Orbiter (MRO) spacecraft payload Context Camera (CTX) images. In this procedure, we used ERDAS Imagine for image rectification and mosaicking as a tool for image processing, which is a new and unique method of generating a mosaic of thousands of CTX images to visualize the large-scale areas. The output product will be applicable for mapping of Martian geomorphological features, 2D mapping of the linear feature with high resolution, crater counting, and morphometric analysis to a certain extent.\",\"PeriodicalId\":63246,\"journal\":{\"name\":\"地质学期刊(英文)\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"地质学期刊(英文)\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.4236/ojg.2021.118020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"地质学期刊(英文)","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.4236/ojg.2021.118020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Method of Mosaicking Context Camera (CTX) Images for the Geomorphological Study of Martian Landscape
Various spacecraft and satellites from the world’s best space agencies are exploring Mars since 1970, constantly with great ability to capture the maximum amount of dataset for a better understanding of the red planet. In this paper, we propose a new method for making a mosaic of Mars Reconnaissance Orbiter (MRO) spacecraft payload Context Camera (CTX) images. In this procedure, we used ERDAS Imagine for image rectification and mosaicking as a tool for image processing, which is a new and unique method of generating a mosaic of thousands of CTX images to visualize the large-scale areas. The output product will be applicable for mapping of Martian geomorphological features, 2D mapping of the linear feature with high resolution, crater counting, and morphometric analysis to a certain extent.