The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domainsCovers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarkingReviews hardware implementation of watermarkingDiscusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithmsIncludes a case study along with its MATLAB code and simulation results
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
