The Problem of Sparse Image Coding
Journal of Mathematical Imaging and Vision
vol. 17 (2), pp. 87-106
PDF
from Kluwer Online
A postscript version is available on request from the author.
An earlier version is available as
Technical Report DIKU-TR-2001-2
Author: Arthur E.C. Pece
E-mail: aecp@diku.dk
Abstract
Linear expansions of images find many applications in image processing
and computer vision. Overcomplete expansions are often desirable,
as they are better models of the image-generation process.
Such expansions lead to the use of sparse codes.
However, minimizing the number of non-zero coefficients of linear expansions
is an unsolved problem. In this article, a generative-model framework
is used to analyze the requirements, the difficulty,
and current approaches to sparse image coding.
Related publication by the same author
- A.E.C. Pece, N. Petkov,
Fast atomic decomposition by the inhibition method.
- Proceedings of the 15th
International Conference on Pattern Recognition:
- ICPR 2000,
Barcelona, Spain, September 2-8, 2000, pp.215-218.
-
gzipped Postscript