DocumentCode
843527
Title
A Gaussian derivative-based transform
Author
Bloom, Jeffrey A. ; Reed, Todd R.
Author_Institution
Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
Volume
5
Issue
3
fYear
1996
fDate
3/1/1996 12:00:00 AM
Firstpage
551
Lastpage
553
Abstract
The article describes a new image transform that decomposes an image using a set of Gaussian derivatives. The basis functions themselves have been shown to effectively model the measured receptive fields of simple cells in the mammalian visual cortex. Based on these functions, it can be expected that this transform can provide a mechanism for exploiting the properties of the human visual system in image processing algorithms
Keywords
Gaussian processes; image coding; image reconstruction; transform coding; transforms; visual perception; Gaussian derivative based transform; basis functions; cells; human visual system; image coding; image processing algorithms; image reconstruction; image transform; mammalian visual cortex; measured receptive fields; Brain modeling; Gabor filters; Humans; Image coding; Image processing; Image sequences; Mechanical factors; Polynomials; Quantization; Visual system;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.491330
Filename
491330
Link To Document