Dynamical quantum groups were recently introduced by Etingof and Varchenko as an algebraic framework for studying the dynamical Yang–Baxter equation, which is precisely the Yang–Baxter equation satisfied by 6j-symbols. We investigate one of the simplest examples, generalizing the standard SU(2) quantum group. The matrix elements for its corepresentations are identified with Askey–Wilson polynom...

This paper presents a novel wavelet-based image denoising algorithm under overcomplete expansion. In order to optimize the denoising performance, we make a systematic study of both signal and noise characteristics under overcomplete expansion. Highband coefficients are viewed as the mixture of non-edge class and edge class observing different probability models. Based on improved statistical mo...

Wavelet techniques have become an attractive and efficient tool in function estimation. Given noisy data, its discrete wavelet transform is an estimator of the wavelet coefficients. It has been shown by Donoho and Johnstone (Biometrika 81 (1994) 425-455) that thresholding the estimated coefficients and then reconstructing an estimated function reduces the expected risk close to the possible min...

In order to provide an efficient way to processing with limited resources, we propose a novice wavelet coder that operates with little memory usage on the portable embedded system. In order to reduce redundancy in coding process caused by repetitive scanning of wavelet coefficients, the proposed coder uses a 2-D the Significance Coefficient Array (SCA) which records the bit-level information of...

Classification of multi class images is very enviable for different recognition. This is affected by many factors such as noise, blur, low illumination, complex background, occlusion etc. Noise is one of the major factors causing degradation of the classification performance. This paper proposes an efficient method for classification of multi class object images which are corrupted by Gaussian ...

One of the advantages of the Discrete Wavelet Transform (DWT) compared to Fourier Transform (e.g. Discrete Cosine Transform DCT) is its ability to provide both spatial and frequency localization of image energy. However, WT coefficients, like DCT coefficients, are defined by magnitude as well as sign. While algorithms exist for the coding of wavelet coefficients magnitude, there are no efficien...

We present a steganalysis scheme for LSB matching steganography based on feature vectors extracted from integer wavelet transform (IWT). In integer wavelet decomposition of an image, the coefficients will be integer, so we can calculate co-occurrence matrix of them without rounding the coefficients. Before calculation of co-occurrence matrices, we clip some of the most significant bitplanes of ...

This paper proposes wavelet-based moving object segmentation using change detection and background registration technique. The inter-frame difference for detecting change was calculated by using high frequency coefficients in wavelet subbands. The background was constructed with low frequency wavelet coefficients which were the approximated version of the original image. Combining detected chan...

This study proposes and justifies a Bayesian approach to modeling wavelet coefficients and finding statistically significant features in wavelet power spectra. The approach utilizes ideas elaborated in scale-space smoothing methods and wavelet data analysis. We treat each scale of the discrete wavelet decomposition as a sequence of independent random variables and then apply Bayes’ rule for con...

The problem of change detection of time series with abrupt and smooth changes in the spectral characteristics is addressed. We first review the main characteristics of the discrete wavelet transform and the maximal overlap discrete wavelet transform. An algorithm for sequential change detection in time series is then reported based on the maximal overlap discrete wavelet transform and Bayesian ...