Adaptive Non-separable Wavelet Transform via Lifting and its Application to Content-Based Image Retrieval

ABSTRACT:

We present in this paper a novel way to adapt a multidimensional wavelet filter bank, based on the nonseparablelifting 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 (mathtilde N??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 mathtilde N?? and N?? , respectively. However, in order tointroduce 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, andwhatever 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 complexwavelet transform, an overcomplete nonseparable wavelet transform.

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