Super-Resolution for Remote Sensing (Unsupervised and Semi-Supervised Learning)
Super-Resolution for Remote Sensing (Unsupervised and Semi-Supervised Learning) by Michal Kawulok, Jolanta Kawulok, Bogdan Smolka
English | October 15, 2024 | ISBN: 3031681053 | 398 pages | MOBI | 30 Mb
English | October 15, 2024 | ISBN: 3031681053 | 398 pages | MOBI | 30 Mb
This book provides a comprehensive perspective over the landscape of super-resolution techniques developed for and applied to remotely-sensed images. The chapters tackle the most important problems that professionals face when dealing with super-resolution in the context of remote sensing. These are: evaluation procedures to assess the super-resolution quality; benchmark datasets (simulated and real-life); super-resolution for specific data modalities (e.g., panchromatic, multispectral, and hyperspectral images); single-image super-resolution, including generative adversarial networks; multi-image fusion (temporal and/or spectral); real-world super-resolution; and task-driven super-resolution. The book presents the results of several recent surveys on super-resolution specifically for the remote sensing community.
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