Artificial Intelligence Techniques for Satellite Image Analysis [electronic resource] / edited by D. Jude Hemanth.

1. Heightening satellite image display via mobile augmented reality - a cutting-edge planning model -- 2. Multithreading Approach for clustering of Multi-Plane Satellite Images -- 3. Classification of field level crop types with a time series satellite data using Deep Neural Network -- 4. Detection of ship from satellite images using deep convolutional neural networks with improved median filter -- 5. Artificial Bee Colony optimized contrast enhancement for satellite image fusion -- 6. Effective transform domain denoising of oceanographic sar images for improved target characterization -- 7. Fused segmentation algorithm for the detection of nutrient deficiency in crops using SAR images -- 8. Detection of natural features and objects in satellite images by semantic segmentation using neural networks -- 9. Change Detection of Tropical Mangrove Ecosystem with Subpixel Classification of Time Series Hyperspectral Imagery -- 10. Crop Classification and Mapping for Agricultural Land from Satellite Images -- 11. Next Generation Artificial Intelligence Techniques for Satellite Data Processing -- 12. A wavelet transform applied spectral index for effective water body extraction from moderate resolution satellite images.

The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing. .