In this paper, we propose a novel wavelet coefficient threshold (WCT) depended on both time and frequency information for providing robustness to non-stationary and correlated noisy environments. A perceptual wavelet filter-bank (PWFB) is firstly used to decompose the noisy speech signal into critical bands according to critical bands of psycho-acoustic model of human auditory system. The estim...

i I affirm, that I have created this diploma thesis on my own, with the exclusive usage of the refer-enced literature. Contents Introduction 1 1 Mathematical background 3 1. A Test images 77 iii iv CONTENTS Introduction The discrete wavelet transformation (see section 1.1 for details) has become a very popular tool to preprocess images to improve the performance of many tasks in the field of an...

In the last decade, multiscale techniques for gray-level texture analysis have been intensively studied. In this paper, we aim on extending these techniques to color images. We introduce wavelet energycorrelation signatures and we derive the transformation of these signatures upon linear color space transformations. Classi cation experiments demonstrate that the wavelet correlation features con...

This paper puts forward a simple algorithm to make color images lighter based on Wavelet transformation and histogram smoothing. This algorithm uses HIS space which is based on human visual features. Without changing hue, it can conduct histogram smoothing in low brightness frequency domain through wavelet decomposition and make the images lighter, which at the same time avoids vagueness of det...

In this paper, a novel method to recognize defect regions of apples based on Gabor wavelet transformation and SVM using machine vision is proposed. The method starts with background removal and object segmentation by threshold. Texture features are extracted from each segmented object by using Gabor wavelet transform, and these features are introduced to support vector machines (SVM) classifier...

The Adaptive Wavelet Image Compression (AWIC) algorithm is a fast, simple waveletbased image compression technique that follows the classical paradigm of image transformation, quantization, and entropy encoding. A key component of AWIC is a technique of channel symbol definition that provides greatly reduced Huffman table encoding costs, allowing optimal Huffman codewords to be generated and us...

In recent years, wavelet shrinkage has become a very appealing method for data denoising and density function estimation. In particular, Bayesian modelling via hierarchical priors has introduced novel approaches for Wavelet analysis that had become very popular, and are very competitive with standard hard or soft thresholding rules. In this sense, this paper proposes a hierarchical prior that i...

An approach for Fusarium diseased corn kernels recognition based on wavelet continuous transformation and probabilistic neural network (PNN) classification is presented in the paper. The near infrared diffuse reflectance characteristics are used as base for features extraction. The spectral data are fitted using continuous wavelet mexican hat transformations and their parameters are used for cl...

i I affirm, that I have created this diploma thesis on my own, with the exclusive usage of the refer-enced literature. Contents Introduction 1 1 Mathematical background 3 1. A Test images 77 iii iv CONTENTS Introduction The discrete wavelet transformation (see section 1.1 for details) has become a very popular tool to preprocess images to improve the performance of many tasks in the field of an...

This paper describes a method to decompose multi-scale information from different source medical image using wavelet transformation. The data fusion between CT image and MRI image is implemented based on the coefficients fusion rule which included choice of regional variance and weighted average wavelet information. The result indicates that this method is better than WMF, LEF and RVF on fusion...