SUPER-RESOLUTION FOR SENTINEL-2 IMAGES

Super-resolution of Defocus Blurred Images

Super-resolution is a process that combines information from some low-resolution images in order to produce an image with higher resolution. In most of the previous related work, the blurriness that is associated with low resolution images is assumed to be due to the integral effect of the acquisition device’s image sensor. However, in practice there are other sources of blurriness as well, inc...

Super-Resolution of Sentinel-2 Images: Learning a Globally Applicable Deep Neural Network

The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance – GSD) bands to 10 m GSD, so as to obtain a complete data cube at the maximal sensor resolution. We employ a state-of-the-art convolutional neural networ...

Super-resolution reconstruction for tongue MR images

Magnetic resonance (MR) images of the tongue have been used in both clinical medicine and scientific research to reveal tongue structure and motion. In order to see different features of the tongue and its relation to the vocal tract it is beneficial to acquire three orthogonal image stacks-e.g., axial, sagittal and coronal volumes. In order to maintain both low noise and high visual detail, ea...

Sparsity-Based Super Resolution for SEM Images

The scanning electron microscope (SEM) is an electron microscope that produces an image of a sample by scanning it with a focused beam of electrons. The electrons interact with the atoms in the sample, which emit secondary electrons that contain information about the surface topography and composition. The sample is scanned by the electron beam point by point, until an image of the surface is f...

Super-resolution for unregistered satellite images