Title :
Multi-Vector Color-Image Filters
Author_Institution :
Essex Univ., Colchester
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
The linear filtering of color images using hypercomplex convolution and Fourier transforms provides a holistic treatment of color by representing pixels as 3-space vector quantities within the quaternion algebra. But, this technique is limited to images with at most three channels of information, e.g., RGB images. Linear filtering of color images by representing color pixels as multi-vectors embedded in a geometric algebra is presented. This multi-vector representation has similar convolution and Fourier transforms as the quaternion based filters, but provides an avenue for multi-spectral images composed of more than three channels.
Keywords :
Fourier transforms; algebra; convolution; image colour analysis; image representation; 3-space vector quantity; Fourier transforms; geometric algebra; hypercomplex convolution; image pixel represention; linear image filtering; multi vector color-image filters; quaternion algebra; Algebra; Color; Convolution; Fourier transforms; Maximum likelihood detection; Multispectral imaging; Nonlinear filters; Pixel; Quaternions; Vectors; Color Image; Convolution Filtering; Geometric Algebra; Multi-vector; Spatio-Color Filtering;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379811