What is super-resolution reconstruction?
The aim of the super-resolution reconstruction (SRR) techniques is to improve the quality and increase the resolution of images (upscale images) while restoring as many details as possible from the source image. Additional goals include: preserving sharp edges, limiting the number of unwanted image distortions after the transformations, producing a visually appealing image.
The SRR developed by KP Labs is based on deep neural networks and advanced statistical methods offering top reconstruction performance. What’s more, application of evolutionary algorithms allowed us to improve these methods further.
Imaging from nano-satellite constellations or other low to medium resolution imagery
Machine vision systems
Production monitoring and inspection and control systems
Bar codes (1D) or QR codes (2D) and OCR applications