In this paper we present a new technique for watermarking in the hyperanalytic wavelet domain. This has the advantage of better directional selectivity and shift invariance compared to the classical wavelet filter. The watermark is inserted into all levels of decomposition using a perceptual mask conceived by the authors. We compare this technique with two systems in the DWT domain, and show it...

We present a novel object-based spatiotemporal (3-D) subband/wavelet coding scheme for very low bit-rate video compression. First, the image sequence is segmented into objects based on motion and color. The objects are then independently decomposed by sub-band/wavelet analysis, both in the temporal and spatial domain. The temporal analysis is greatly facilitated over existing methods by the obj...

Introduction PACT Abstract Wavelet packets represent a generalization of the method of multiresolution decomposition and comprise the entire family of subband coded (tree) decompositions. Wavelet packet best basis selection has become a popular method in image compression, whereas the local discriminant bases algorithm is a relatively new feature extraction method based on a wavelet packet expa...

Wavelet estimation plays an important role in many seismic processes like impedance inversion, amplitude versus offset (AVO) and full waveform inversion (FWI). Statistical methods of wavelet estimation away from well control are a desirable tool to support seismic signal processing. One of these methods based on Homomorphic analysis has long intrigued as a potentially elegant solution to the wa...

This paper presents a new wavelet-network-based technique for 1D and 2D functions’ approximation. Classical training algorithms start with a predetermined network structure which can be either insufficient or overcomplicated. Furthermore, the resolutions of wavelet networks training problems by gradient are characterized by their noticed inability to escape of local optima. The main feature of ...

This paper presents a statistical learning algorithm based on Support Vector Machines (SVMs) for the classification of Malayalam Consonant – Vowel (CV) speech unit in noisy environments. We extend SVM for multiclass classification using Decision Directed Acyclic Graph Support Vector Machine (DDAGSVM) algorithm. For classification, acoustical features are extracted using Wavelet Transform (WT) b...

Wavelet shrinking algorithms for image de-noising replace wavelet coeecients with absolute values below a certain threshold by zero and keep or shrink the other coeecients. This is basically a local procedure, since wavelet coeecients characterize the local regularity of a function. In spite of a careful choice of the threshold, this method does not take into account the geometrical structure o...

Image fusion deals with the integration of multi modal images from various sensors, with visual and infrared, to MMW images, aiming at achieving improved image quality to better support improved image classification, monitoring, surveillance and etc. The main goal of this paper is to introduce a new approach to fuse visual image and infrared images by complex wavelet taking depth of focus into ...

The soft thresholding function has been used in wavelet packet structure to efficiently remove background noises. However, it suffers from both serious residual noise and speech distortion. The classical method that estimates the threshold of wavelet coefficients assumes the corrupted noise to be white Gaussian noise. In fact, the noise is generally not white in practical environments. This pap...

due to the remarkable advantages of wavelet transformation, this technique is now very common in gravity analysis. in this research the green’s function occurring in the poisson potential field theory is used to construct non-orthogonal, non-compact, continuous wavelets. this kind of wavelet is directly corresponded to upward continuation procedure. simple geometrical forward models such as sph...