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In this paper, we discuss a face recognition scheme by subspace analysis of 2D log-Gabor wavelets features. In which, an input face image is firstly decomposed with a set of two dimensional log-Gabor wavelets (2D-LGWs) localized with respect to spatial location, orientation and frequency. Based on complex responses of filters, local energy model (LEM) is used to represent log-Gabor features (LGFs)...
In this paper, we propose a new multiscale version 3D surfacelet tranform, named wavelet-based surfacelet transform (WBST). The surfacelet transform (ST) is constructed by combining the 3D directional filter banks with a multiscale pyramid structure. But the redundancy of the pyramid structure will affects the performance of ST in some redundant-sensitivity applications. To avoid the redundancy, we...
We propose a novel texture feature extraction technique based on coefficients' co-occurrence histogram of discrete wavelet frame transformed image, which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. It is not independently utilizing the information of each subband coefficient. The classification...
This paper proposes a novel idea based feature selection in the verification system of palmprint, which can realize the specific feature selection for different user using genetic algorithm (GA). In the stage of enrollment, discrete wavelet transforms (DWT) and statistical methods are first used for feature extraction. Then GA is employed for feature selection, which means that each user has a specific...
A novel inter-scale correlation image denoising method based on dual-tree M-band wavelet (DTT) is proposed in this paper. Dual-tree M-band wavelet transform is a shift-invariant, multi-scale and multi-direction transform based on a Hilbert pair of wavelets initially proposed by N. Kingsbury. Improving upon Xu??s denosing algorithm based on wavelet inter-scale correlation, a new correlation modeling...
Discriminative common vectors is one of the most successful methods which overcome the small sample size case in Fisher??s linear discriminant analysis. But when we directly use DCV to reduce the dimensions of the ear images, the computational expense of training is still relatively large. A new method is proposed in this paper that the low frequency sub-images are obtained by utilizing two-dimensional...
In this paper, the 3-D wavelet-fractal coding was used to compress the hyperspectral remote sensing image. The classical eight kinds of affine transformations in 2-D fractal image compression were generalized to nineteen for the 3-D fractal image compression. Hyperspectral image date cube was first translated by 3-D wavelet and then the 3-D fractal compression coding was applied to lowest frequency...
This paper proposes a novel method on synthetic aperture radar (SAR) Image denoising, which is based on context modeling combined with multiscale orthogonal bandlet coefficients. For the main influence of SAR image is multiplicative speckle noise, the logarithm uniform transform is used to convert it to additive noise. In this paper, the multiscale orthogonal bandlet transform is applied to noisy...
In this paper, a synergy of signal processing techniques and intelligent strategies is applied in order to identify different types of human brain tumours, so that to help to confirm the histological diagnosis. The wavelet-SVM (support vector machine) classifier merges wavelet transform to reduce the size of the biomedical spectra and to extract the main features, with SVM to classify them. The influence...
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