A new wavelet-based texture descriptor for image retrieval
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Wavelet steerability and the higher-order Riesz transform
IEEE Transactions on Image Processing
An effective content-based image retrieval system by hierachical segmentation
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Novel face recognition approach based on steerable pyramid feature extraction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Lightweight probabilistic texture retrieval
IEEE Transactions on Image Processing
International Journal of Computer Vision
Journal of Visual Communication and Image Representation
Bi-hierarchy medical image registration based on steerable pyramid transform
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
Statistical texture retrieval in noise using complex wavelets
Image Communication
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This paper presents a novel rotation-invariant image retrieval scheme based on a transformation of the texture information via a steerable pyramid. First, we fit the distribution of the subband coefficients using a joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior. Then, we apply a normalization process in order to Gaussianize the coefficients. As a result, the feature extraction step consists of estimating the covariances between the normalized pyramid coefficients. The similarity between two distinct texture images is measured by minimizing a rotation-invariant version of the Kullback-Leibler Divergence between their corresponding multivariate Gaussian distributions, where the minimization is performed over a set of rotation angles