Fourier transform magnitudes are unique pattern recognition templates
Biological Cybernetics
A friendly guide to wavelets
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition Robust Under Translations, Deformations, and Changes in Background
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Image Reconstruction from Gabor Magnitudes
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Robust classification of hand postures against complex backgrounds
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Gabor wavelet representation for 3-D object recognition
IEEE Transactions on Image Processing
Face authentication with Gabor information on deformable graphs
IEEE Transactions on Image Processing
What is the optimal architecture for visual information routing?
Neural Computation
A differential model of the complex cell
Neural Computation
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We present an analysis of the representation of images as the magnitudes of their transform with complex-valued Gabor wavelets. Such a representation is a model for complex cells in the early stage of visual processing and of high technical usefulness for image understanding, because it makes the representation insensitive to small local shifts. We show that if the images are band limited and of zero mean, then reconstruction from the magnitudes is unique up to the sign for almost all images.