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Super-Resolution Image Reconstruction (SRIR)
A practical, robust, low computational overhead algorithm to obtain high resolution (HR) images from low resolution (LR), under-sampled digital imaging equipment.
The US Army’s patented algorithm effectively increases the resolution of the reconstructed output image using the existing imaging device from a sequence of low resolution, under sampled, imagery. By removing aliasing due to under-sampling, SRIR can also improve range performance of the sensor.
SRIR exploits the subpixel movement of an image sequence. When LR images have subpixel shifts between successive frames, they convey different information about the same scene. SRIR takes advantage of this distinct information and fuses the information from the LR frames during reconstruction to generate a high quality HR image of the true scene. Enhanced performance can be obtained using existing hardware. The Army’s method can accommodate subpixel movement of an unknown nature such as natural jitter. It also requires very few input images: 4 frames for 2X linear (4X pixel) resolution improvement.
- Few frames: Low computational overhead, fast processing, realistic mimicking of fast moving targets
- Uses subpixel movement of unknown nature: Easy to implement, examples include natural jitter from a moving platform and expansion and contraction of blood vessels
- Versatile: Tested by inventor on video, forward-looking IR, and flash LADAR; many other applications possible including mobile phones, medical imaging, remote sensing, target recognition, biometric recognition, and industrial inspection
- Multiple implementation options: Currently written in MatLab; can be built into FPGAs and FFT chips, or distributed as stand alone or C shared library
- Available for license and commercialization – except for the field of law enforcement. One issued US patent (7,602,997) and one published US patent application (2010/0067822)
- Peer-reviewed journal articles available
- Potential for R&D collaboration with inventor