Single Image Resolution Enhancement
Super-resolution is the process of increasing the resolution of a low-resolution image. Manifold techniques have been used for super-resolution to enhance image, photo, or video quality, but they are often computationally demanding due to the complexity of the underlying algorithm. MSU researchers have developed a novel method for single image super-resolution, requiring little computational complexity and meeting highest quality standards at a significantly lower cost.
Description of Technology
This technology is an algorithm for linear approximation of a lower dimension manifold using sparse subspace clustering for the purpose of super-resolution or the up-scaling of a single image. Our technology yields comparable if not better image enhancement results than current technique with significantly less computational requirements, thus lowering computational cost.
- Fast – less computational time processing images
- Low cost – very cost-effective due to less computational complexity and shorter processing time
- Image Super Resolution – cameras, etc.
- High definition TV – upscaling video, lower resolution content
- Image/Video quality enhancement
- Medical Imaging – tomography, MRI etc.
- Satellite imaging
Licensing Rights Available
Full licensing available
Inventors: Chinh Dang, Hayder Radha
Tech ID: TEC2014-0006
For Information, Contact:
Michigan State University