Rob A. Zuidwijk CWI E-mail: [email protected] Url: http://www.cwi.nl/cwi/projects/wavelets.html November 6, 1997 Abstract In this lecture, the continuous wavelet transform will be discussed and some attention will be given to the discrete wavelet transform. Finally, wavelet transforms on multidimensional data will be considered. The set-up of the lecture is as follows: 1. The continuous wavelet t...

The use of high performance computers for wavelet and wavelet packet based image coding is discussed. After a short description of wavelet and wavelet packet methods the existing literature concerning vector, parallel and VLSI wavelet transforms is reviewed. In the following an algorithm for wavelet packet best basis selection on moderate parallel MIMD architectures is introduced and an impleme...

In this paper, we propose a new postprocessing method for low bit-rate wavelet-based image coding which uses the technique of wavelet modulus maximum representation (WMMR). The edge degradation from wavelet-based coding is discussed under the overcomplete wavelet expansion, and interpreted as the distortion of wavelet modulus maxima, i.e., magnitude decays. Based on the empirical analysis and e...

Parameterized wavelet filters and wavelet packet subband structures are discussed to be used as key dependent wavelet transforms in order to enhance the security of wavelet based hashing schemes. Experiments show that key dependency and keyspace of the hashing scheme considered have been significantly improved. The attack resistance could only be slightly enhanced by using parametrized wavelet ...

In this paper, we study the unconditional convergence of wavelet expansions with Lipschitz wavelets. Especially with the Strömberg wavelet, we shall construct a counter example which shows that uniformly convergent wavelet expansions even for continuous functions do not always converge unconditionally in L∞(R). KeywordsUnconditional Convergence, Wavelet Expansion, Strömberg Wavelet. AMS Mathema...

Digital watermarking is a technique for embedding information in to cover media to prove ownership. It became very important in the number of application areas such as copyright protection, fingerprinting, broadcast monitoring, and medical application. During the last several years, various watermarking techniques have been proposed by different authors. Wavelet based watermarking is gaining mo...

Both wavelet denoising and denosing methods using the concept of sparsity are based on softthresholding. In sparsity based denoising methods, it is assumed that the original signal is sparse in some transform domains such as the wavelet domain and the wavelet subsignals of the noisy signal are projected onto `1-balls to reduce noise. In this lecture note, it is shown that the size of the `1-bal...