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 classification of stitched and remotely sensed images.The first chapter discusses the important terminologies in remote sensing, types of remotely sensed images, and their characteristics. The second chapter introduces the texture and applications of texture analysis. The third chapter presents a detailed literature survey citing papers related to texture analysis and image processing. The fourth chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images. The fifth chapter focuses on texture-based classification and texture-based segmentation. The concepts are illustrated with pseudo-codes of various basic texture models. The sixth chapter describes five supervised and two unsupervised classifiers. The experimental results obtained with a basic texture model (Local Binary Pattern) along with the classifiers are explained through the relevant pseudo-codes. The seventh chapter analyzes the issue and challenges associated with the texture-based classification of remotely sensed images. It also illustrates with pseudo-codes how texture-based classification of remotely sensed images can be performed with the help of a proposed model by the author that addresses the challenges discussed before. The eighth chapter describes performance metrics associated with texture-based classification and segmentation.This book is useful for both undergraduate students in Computer Science and Civil Engineering, as well as postgraduates who plan to do research or project work in digital image processing, especially in satellite image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab pseudo-codes listed. In short, the book will be a hotcake for growing academicians to gain expertise in their area of specialization and potential students who aim at gaining in-depth knowledge in the subject through practical implementations.