Theory and application of general linear image processing
1 Ecole Nationale Supérieure des Mines de Saint-Etienne, CIS-LPMG/CNRS, Saint-Etienne Cedex 2, France
2 Department of Electronic Engineering, La Trobe University, Bundoora, VIC 3086, Australia
3 Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA
EURASIP Journal on Advances in Signal Processing 2012, 2012:21 doi:10.1186/1687-6180-2012-21Published: 7 February 2012
First paragraph (this article has no abstract)
Image modeling in terms of physical/mathematical formation and the human visual system plays an important role in developing new image processing techniques. Parameters such as scale, orientation, texture, morphology, and color must be taken into consideration in order to solve complicated image processing problems efficiently. Although the classical linear image processing (CLIP) approach has played a central role in image processing, it is not necessarily the best and even the right choice. General linear image processing (GLIP) approaches based on different image modeling techniques have been studied to overcome some of the problems associated with CLIP. Indeed, using general linear algebra, it is possible to develop entirely new general linear operators and transforms. It is even possible to define entirely new general linear operations (addition, scalar multiplication, convolution, etc.) in order to describe how images are combined, amplified, transformed, analyzed, compared, and measured.