Image analysis using a generalised wavelet transformA. D. Calway, Image analysis using a generalised wavelet transform. IEE Colloquium on Applications of Wavelet Transforms in Image Processing, pp. 1–8. January 1993. PDF, 85 Kbytes.
This paper gives an overview of a novel form of wavelet transform (WT) in which the link between scale and frequency is removed, and which provides a degree of shift invariance. Known as the Multiresolution Fourier Transform (MFT), this resembles a stack of windowed Fourier transforms (WFT) 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, yielding a flexibility not possessed by existing WTs. 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.