| 书目名称 | Land Cover Classification of Remotely Sensed Images |
| 副标题 | A Textural Approach |
| 编辑 | S. Jenicka |
| 视频video | |
| 概述 | The book helps the reader in implementing the concepts through the Matlab source codes listed.The book is immensely useful for Computer Science and Civil Engineering undergraduates as well post-gradua |
| 图书封面 |  |
| 描述 | .The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. .The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab sou |
| 出版日期 | Book 2021 |
| 关键词 | Image Processing; Texture Analysis; Remotely Sensed Images; Texture Models; Segmentation; remote sensing/ |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-66595-1 |
| isbn_softcover | 978-3-030-66597-5 |
| isbn_ebook | 978-3-030-66595-1 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 20:06:58
