Written using clear and accessible language, this useful guide discusses fundamental concepts and practices of multi-resolution image fusion.Presenting new advances in the field, this text will be a valuable reference for the students and researchers of image processing, multi-spectral imaging and remote sensing. It discusses tools and techniques of multi resolution image fusion with the necessary mathematical background.Presenting new advances in the field, this text will be a valuable reference for the students and researchers of image processing, multi-spectral imaging and remote sensing. It discusses tools and techniques of multi resolution image fusion with the necessary mathematical background.Written in an easy-to-follow approach, the text will help the readers to understand the techniques and applications of image fusion for remotely sensed multi-spectral images. It covers important multi-resolution fusion concepts along with the state-of-the-art methods including super resolution and multi stage guided filters. It includes in depth analysis on degradation estimation, Gabor Prior and Markov Random Field (MRF) Prior. Concepts such as guided filter and difference of Gaussian are discussed comprehensively. Novel techniques in multi-resolution fusion by making use of regularization are explained in detail. It also includes different quality assessment measures used in testing the quality of fusion. Real-life applications and plenty of multi-resolution images are provided in the text for enhanced learning.Preface; Acknowledgement; Dedication; List of figures; List of tables; 1. Introduction; 2. Literature review; 3. Image fusion using different edge preserving filters; 4. Image fusion: model based approach with degradation estimation; 5. Use of self-similarity and Gabor Prior; 6. Image fusion: application to super-resolution of natural images; 7. Conclusions and directions for future research; Bibliography; Index.