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
fDate :
3/1/1996 12:00:00 AM
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;
Journal_Title :
Image Processing, IEEE Transactions on
