Abstract—A multi-scale texture segmentation algorithm for SAR images based on the discrete wavelet transform is presented. Responses from different sub-bands are used to form a feature vector for each pixel position that is the input to the classification scheme. To further improve the classification results, the tree-structured wavelet packet transform is used to automatically identify a suita...

The presence of speckle in Synthetic Aperture Radar (SAR) images makes the segmentation of such images difficult A novel method for automatic segmentation of SAR images is proposed. Firstly, a wavelet packet based texture feature set is derived. It consists of the energy of the feature subimages obtained by the overcomplete wavelet packet decomposition of local areas in SAR image, where the dow...

A multi-parameter feature and recognition method is established for GPR underground targets based on multi-feature information fusion ideas specific to complexity and diversity of detecting environment and underground media as well as non-stationarity and aperiodicity of GPR echo signals. This method carries out multi-parameter feature fusion by selecting power spectrum, wavelet packet energy s...

The aircraft passive sonic detects and identification technology as a traditional means of reconnaissance is an important component of airborne early-warning system. Using the sound wave what the acoustic targets produces in the rate process, to identify the targets is the basic task of passive acoustic detection system. This study using modern signal processing method studies the wavelet trans...

This paper introduces the use of Relevance Vector Machines (RVMs) for content based image classification and compares it with the conventional Support Vector Machine (SVM) approach. Different wavelet kernels are included in the formulation of the RVM. We also propose a new wavelet based feature extraction method that extracts lesser number of features as compared to other wavelet based feature ...

This research presents the multi –modal biometric system for iris and fingerprint This paper presents the Feature level fusion using wavelet for combining two unimodal biometric system. Gabor transform is used for feature extraction and wavelet transformation for fusion of iris and fingerprint. The system applied artificial neural network technique for recognizing whether the user is genuine (a...

There is a high demand for eeective and precise tools for users to search, browse, and interact with image databases and do so in a timely manner. Automatic feature extraction is a crucial part for any such retrieval systems. Current methods for feature extraction suuer from two main problems: rst, many methods do not retain any spatial information, and second, the problem of invariance with re...

In this paper we present a new wavelet domain technique for texture analysis and test of pattern replicability. The main property of the proposed features is that they measure texture quality along the most important perceptual dimensions. In other words, we quantify and classify textures according to their directionality, symmetry, regularity and type of regularity. After the feature extractio...

In this work. we present a novel method of object recognition and feature generation based on multiscale object descriptions obtained using wavelet networks in combination with morphological filtering. First, morphological filtering techniques are used to obtain structural information about the object. Then, wavelet networks are used to extract or capture geometric information about an object a...

Inspired by both the multilayer perceptron (MLP) and wavelet decomposition, Zhang and Benveniste proposed the wavelet MLP (W-MLP), which has been usedfor time series prediction. The wavelet packet MLP (WP-MLP) is an MLP with the wavelet packet as a feature extraction method to obtain time-frequency information. The WPMLP has been successfully applied to biomedical, image and speech classificati...