Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Spherical wavelets: efficiently representing functions on the sphere
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Adaptive Wavelet Transforms for Image Coding Using Lifting
DCC '98 Proceedings of the Conference on Data Compression
A new method of estimating wavelet with desired features from a given signal
Signal Processing - Content-based image and video retrieval
Neville-Lagrange wavelet family for lossless image compression
Signal Processing
Design of Multimodal Dissimilarity Spaces for Retrieval of Video Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of shape similarity measurement methods for spine X-ray images
Journal of Visual Communication and Image Representation
IEEE Transactions on Information Technology in Biomedicine
Wavelet families of increasing order in arbitrary dimensions
IEEE Transactions on Image Processing
Nonlinear multiresolution signal decomposition schemes. II. Morphological wavelets
IEEE Transactions on Image Processing
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
A novel method for image retrieval based on structure elements' descriptor
Journal of Visual Communication and Image Representation
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We present in this paper a novel way to adapt a multidimensional wavelet filter bank, based on the nonseparable lifting scheme framework, to any specific problem. It allows the design of filter banks with a desired number of degrees of freedom, while controlling the number of vanishing moments of the primal wavelet ( Ñ moments) and of the dual wavelet (N moments). The prediction and update filters, in the lifting scheme based filter banks, are defined as Neville filters of order Ñ and N, respectively. However, in order to introduce some degrees of freedom in the design, these filters are not defined as the simplest Neville filters. The proposed method is convenient: the same algorithm is used whatever the dimensionality of the signal, and whatever the lattice used. The method is applied to content-based image retrieval (CBIR): an image signature is derived from this new adaptive nonseparable wavelet transform. The method is evaluated on four image databases and compared to a similar CBIR system, based on an adaptive separable wavelet transform. The mean precision at five of the nonseparable wavelet based system is notably higher on three out of the four databases, and comparable on the other one. The proposed method also compares favorably with the dual-tree complex wavelet transform, an overcomplete nonseparable wavelet transform.