We report on the development of an adaptive wavelet image coder based on stack-run representation of the quantized coefficients. The coder works by selecting an optimal wavelet packet basis for the given image and encoding the quantization indices for significant coefficients and zero runs between coefficients using a 4-ary arithmetic coder. Due to the fact that our coder exploits the redundanc...

In this paper we shortly summarize the many advantages of the discrete wavelet transform in the analysis of time series. The data are transformed into clusters of wavelet coefficients and rate of change of the wavelet coefficients, both belonging to a suitable finite dimensional domain. It is shown that the wavelet coefficients are strictly related to the scheme of finite differences, thus givi...

Fourier transform is applied to detect the direction of stripe noise before de-noising, which is advantageous for selecting the corresponding detail coefficients for threshold quantization after stationary wavelet transform. Depending on the direction of stripe noise, the corresponding detail coefficients contain stripe noise need to be removed, while retaining the approximate coefficients and ...

This paper presents a state-of-the-art adaptive wavelet-based denoising method with edge preservation. More specifically, a redundant discrete dyadic wavelet transform (DDWT) is performed on the noisy image to get the wavelet frame decomposition at different scales. Based on the Lipschitz regularity theory, correlation analysis across scales is performed to detect the significant coefficients f...

There exist efficient methods to compute the wavelet coefficients of a function f(t) from its point samples f ( T [n + τ ] ) , n ∈ N. However, in many applications the available samples are average samples of the type ∫∞ −∞ f ( T [t + n + τ ] ) u(t)dt, where the averaging function u(t) reflects the characteristic of the acquisition device. In this work, methods to compute the coefficients in a ...

The paper presents a novel despeckling method, based on Daubechies complex wavelet transform, for medical ultrasound images. Daubechies complex wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. A wavelet shrinkage factor has been derived to estimate the noise-free wa...

The present paper is intended to present a robust multiplicative video watermarking scheme. In this regard, the video signal is segmented into 3-D blocks like cubes, and then, the 3-D wavelet transform is applied to each block. The low frequency components of the wavelet coefficients are then used for data embedding to make the process robust against both malicious and unintentional attacks. Th...

We study the scaling behavior of the fluctuations, as extracted through wavelet coefficients based on discrete wavelets. The analysis is carried out on a variety of physical data sets, as well as Gaussian white noise and binomial multi-fractal model time series and the results are compared with continuous wavelet based average wavelet coefficient method. It is found that high-pass coefficients ...

The redundancy of continuous wavelet transforms implies that the wavelet coefficients are not independent of each other. This interdependence allows the reconstruction or approximation of the wavelet transform, and of the original field, from a subset of the wavelet coefficients. Contrasting with lines of modulus maxima, known to provide useful partition functions and some data compaction, the ...

Wavelet packets are an effective representation tool for adaptive waveform analysis of a given signal. We first combine the wavelet packet representation with zerotree quantization for image coding. A general zerotree structure is defined which can adapt itself to any arbitrary wavelet packet basis. We then describe an efficient coding algorithm based on this structure. Finally, the hypothesis ...