Artificial Intelligence Techniques for Satellite I

  • 4h 17m
  • D. Jude Hemanth
  • Springer
  • 2019

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.

In this Book

  • Heightening Satellite Image Display via Mobile Augmented Reality – A Cutting-Edge Planning Model
  • Multithreading Approach for Clustering of Multiplane Satellite Images
  • Classification of Field-Level Crop Types with a Time Series Satellite Data Using Deep Neural Network
  • Detection of Ship from Satellite Images Using Deep Convolutional Neural Networks with Improved Median Filter
  • Artificial Bee Colony-Optimized Contrast Enhancement for Satellite Image Fusion
  • Effective Transform Domain Denoising of Oceanographic SAR Images for Improved Target Characterization
  • Fused Segmentation Algorithm for the Detection of Nutrient Deficiency in Crops Using SAR Images
  • Detection of Natural Features and Objects in Satellite Images by Semantic Segmentation Using Neural Networks
  • Change Detection of Tropical Mangrove Ecosystem with Subpixel Classification of Time Series Hyperspectral Imagery
  • Crop Classification and Mapping for Agricultural Land from Satellite Images
  • Next-Generation Artificial Intelligence Techniques for Satellite Data Processing
  • A Wavelet Transform Applied Spectral Index for Effective Water Body Extraction from Moderate-Resolution Satellite Images