Title :
Image analysis using a generalised wavelet transform
Author_Institution :
Dept. of Comput. Sci., Warwick Univ., Coventry, UK
Abstract :
In a novel form of wavelet transform (WT) the link between scale and frequency is removed, which provides a degree of shift invariance. Known as the multiresolution Fourier transform (MFT), this resembles a stack of windowed Fourier transforms (WET) in which the window size is varied systematically to give a multiresolution representation of the space-frequency plane. As such, it constitutes a superset of the WT and WFT, providing a complete representation of the frequency domain at each scale and hence enabling regions to be analysed over a range of frequencies. This has allowed the MFT to be used as the basis for tackling a wide range of problems, including linear feature and curve extraction, texture analysis and stereopsis, and hence provides a framework for a unified approach to image analysis
Keywords :
feature extraction; image processing; image texture; wavelet transforms; curve extraction; frequency domain; generalised wavelet transform; image analysis; linear feature extraction; multiresolution Fourier transform; shift invariance; stereopsis; texture analysis; window size;
Conference_Titel :
Applications of Wavelet Transforms in Image Processing, IEE Colloquium on
Conference_Location :
London