Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the MAP estimator depends on the proposed model for noise-free wavelet coefficients. Thus in the wa...

in this paper, a block-based method in wavelet domain for sar image coding is presented based on the ezbc algorithm. to better preserve edges and textural structure in sar images, instead of using traditional dyadic wavelet transform, a packet wavelet is employed. to improve the efficiency of the ezbc algorithm for sar image coding, a modified version of this algorithm, is proposed. this modifi...

this paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (lssvm). two wavelet selection criteria maximum energy to shannon entropy ratio and maximum relative wavelet energy are used and compared to select an appropriate wavelet for feature extraction. the fault diagnosis method co...

this paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (lssvm). two wavelet selection criteria maximum energy to shannon entropy ratio and maximum relative wavelet energy are used and compared to select an appropriate wavelet for feature extraction. the fault diagnosis method co...

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...

An image compression algorithm based on wavelet packet transform is introduced. The algorithm extends the parent-children link established across dyadic wavelet decomposition bands to a parent-children link across wavelet packet decomposition bands. Then, a method proposed for the efficient encoding of dyadic wavelet transform coefficients [1] is used for encoding of wavelet packet transform co...

The hidden Markov tree (HMT) model is a novel statistical model for signal and image processing in the wavelet domain. The HMT model captures the interscale persistence property of wavelet coefficients, but includes only a tiny intrascale clustering property of wavelet coefficients. In this paper, we propose the contextual hidden Markov tree (CHMT) model to enhance the clustering property of th...

identification of damping parameter is usually more complicated and unreliable comparing to mass or stiffness identification in structural dynamics. there are many factors such as intermolecular friction, coulomb friction and viscous damping affecting the damping mechanisms in a structure. therefore it is difficult, and in some cases impossible, to describe the details of damping mechanisms by ...