Paper
10 February 2012 Application of non-linear transform coding to image processing
Author Affiliations +
Proceedings Volume 8291, Human Vision and Electronic Imaging XVII; 829105 (2012) https://doi.org/10.1117/12.908732
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
Sparse coding learns its basis non-linearly, but the basis elements are still linearly combined to form an image. Is this linear combination of basis elements a good model for natural images? We here use a non-linear synthesis rule, such that at each location in the image the point-wise maximum over all basis elements is used to synthesize the image. We present algorithms for image approximation and basis learning using this synthesis rule. With these algorithms we explore the the pixel-wise maximum over the basis elements as an alternative image model and thus contribute to the problem of finding a proper representation of natural images.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jens Hocke, Erhardt Barth, and Thomas Martinetz "Application of non-linear transform coding to image processing", Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 829105 (10 February 2012); https://doi.org/10.1117/12.908732
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Chemical elements

Image compression

Data modeling

Image processing

Cameras

Nonlinear image processing

Electronic imaging

Back to Top