… cannot work well on certain tasks in remote sensing image processing (eg classification [12] …
Therefore, the data complexity raises new challenges for remote sensing image processing. …

… vision applications and remote sensing (RS) image processing. … learning-based RS image
processing. We identified and … RS image processing tasks (eg, image classification, object …

… remote sensing image processing, including not only optical imagery but also synthetic aperture
radar (SAR) imagery. … , spatial and temporal resolution of remote sensing data, there are …

… aspects of Digital Image Processing which are applied to remote sensing images obtained
from various satellite sensors. In remote sensing, the image processing techniques can be …

… This limits the development and wide application of GPU in remote sensing image
processing. Furthermore, the processing system for remote sensing image processing is closely …

… remote sensing (RS) community. In this letter, we present a framework enabling the use of
DL techniques with RS images … libraries, the RS image processing library Orfeo ToolBox and …

… , process, and interpret images with open-source and commercial image processing and …
We also created the Digital Image Processing Lab Manual so that instructors and students have …

… Although our focus in this book will tend to be on optical remote sensing when demonstrating
image processing and analysis techniques, it is of value at this point to note the other …

… enriching the field of remote sensing (RS) image processing and analysis. Unfortunately, …
approach that enables a joint spectral and spatial information process. A set of 3-D schemes is …

… To regularize this loss and improve training, CNNs [1] are a special type of neural networks
that impose restrictions that make sense in the context of image processing. In these networks…