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Found 8 papers, 1 papers with code
HSTR-Net: Reference Based Video Super-resolution for Aerial Surveillance with Dual Cameras
Aerial surveillance requires high spatio-temporal resolution (HSTR) video for more accurate detection and tracking of objects.
HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance
Wide area surveillance has many applications and tracking of objects under observation is an important task, which often needs high spatio-temporal resolution (HSTR) video for better precision.
Altitude Optimization of UAV Base Stations from Satellite Images Using Deep Neural Network
It is expected that unmanned aerial vehicles (UAVs) will play a vital role in future communication systems.
Light field super resolution through controlled micro-shifts of light field sensor
One drawback of the micro-lens array based light field cameras is low spatial resolution due to the fact that a single sensor is shared to capture both spatial and angular information.
Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks
Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field.
Extracting Sub-Exposure Images from a Single Capture Through Fourier-based Optical Modulation
Through pixel-wise optical coding of images during exposure time, it is possible to extract sub-exposure images from a single capture.
Hybrid Light Field Imaging for Improved Spatial Resolution and Depth Range
While low spatial resolution limits the general purpose use and applicability of light field cameras, narrow baseline limits the depth estimation range and accuracy.
Light Field Stitching for Extended Synthetic Aperture
By merging multiple light fields captured by an MLA based camera, we obtain larger synthetic aperture, which results in improvements in light field capabilities, such as increased depth estimation range/accuracy and wider perspective shift range.
