We propose a large scale terrain adaptive compression method with high compression rate in this paper by using integer wavelet transform combined with restricted quadtree triangulation based on the terrain variation characteristic. By taking advantage of the efficient computing and multi-resolution attributes of our algorithm, we can decompress the wavelet coefficients which indicate the terrai...

In order to get an efficient image representation we introduce a new adaptive Haar wavelet transform, calledTetrolet Transform. Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. The corresponding filter bank algorithm is simple but enormously effective. Numerical results show the strong efficiency of the tetrolet transf...

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. Wavelet transforms have shown promising results for localization in both time and frequency, and hence have been used for image processing applications including noise removal. By using the edge-based denoising and adaptive nonlinear histogram stretchi...

A model of spectral shape analysis in the central auditory system is developed based on neurophysiological mappings in the primary auditory cortex and on results from psychoacoustical experiments in human subjects. The model suggests that the auditory system analyzes an input spectral pattern along three independent dimensions: a logarithmic frequency axis, a local symmetry axis, and a local sp...

The description of 3D shapes using features that possess descriptive power and are invariant under similarity transformations is one of the most challenging issues in contentbased 3D model retrieval. Spherical harmonics-based descriptors have been proposed for obtaining rotation invariant representations. However, spherical harmonic analysis is based on a latitude-longitude parameterization of ...

Discrete wavelet transform is an effective tool to generate scalable stream, but it cannot efficiently represent edges which are not aligned in horizontal or vertical directions, while natural images often contain rich edges and textures of this kind. Hence, recently, intensive research has been focused particularly on the directional wavelets which can effectively represent directional attribu...

Local Binary Pattern (LBP) is a very efficient local descriptor for describing image texture. In this paper, we propose a novel face recognition technique based on wavelet transform and the least square estimator to enhance the classical LBP. First, Wavelet transform is used to decompose a given image into four kinds of frequency images from which the features of that image can be extracted. Th...

This paper proposes a new segmentation technique that combines multiresolution wavelet decompositions with the watershed transform. The wavelet transform is applied to the intensity image, producing detail and approximation coefficients. Gradient magnitudes of the approximation image at the coarsest resolution are computed, and an adaptive threshold is used to remove small gradient magnitudes. ...

This paper presents the design of a hybrid scheme of wavelet transforms and an adaptive Fourier filtering technique for on line fault detection and phasor estimation to fast distance protection of transmission lines. The wavelet transform is used as a signal processing tool. The sampled voltage and current signals at the relay location are decomposed using wavelet transform-Multi Resolution Ana...

In this paper, a new lifting-based shape-direction-adapti discrete wavelet transform (SDA-DWT) which can be used for arbitraril shaped segments is proposed. The SDA-DWT contains three major techniques: the lifting-based DWT, the adaptive directional technique, and the concept of object-based compression in MPEG-4. With SDA-DWT, the number of transformed coefficients is equal to the number of pi...