Two main issues arise when working in the area of texture segmentation: the need to describe the texture accurately by capturing its underlying structure, and the need to perform analyses on the boundaries of textures. Herein, we tackle these problems within a consistent probabilistic framework. Starting from a probability distribution on the space of infinite images, we generate a distribution...

Data embedding and recovery in video watermarking, without loss of quality is a challenging one. A new method for video watermarking is presented in this paper. In the proposed method, we use undecimated wavelet transform. The location for data embedding in the LL subband of wavelet coefficients are selected adaptively based on the energy of high frequency subbands. The decoding is performed ba...

As the number of applications and use of wavelet transforms continues to grow, so does the number of classes and variations of wavelet transform algorithms. All of these algorithms incorporate a filter convolution in some implementation, typically, as part of an iterated filter bank. In contrast to implementations of the classical Fourier transform where there is at most a choice of sign and no...

This paper presents parallel algorithms for computing multi-dimensional wavelet transforms on both shared memory and distributed memory machines. Traditional data partitioning methods for n-dimensional Discrete Wavelet Transforms (DWTs) call for data redistribution once a one dimensional wavelet transform is computed along each dimension. To avoid the data communication inherent in this redistr...

De-noising algorithms based on wavelet thresholding replace small wavelet coeecients by zero and keep or shrink the coeecients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use Generalized Cross Validation. This procedure is fast and does not require an estimation fo...

Ramesh Neelamani December 23, 1998 Project Advisor: Prof. C.S. Burrus ELEC 696 Project Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005. [email protected] Abstract Lifting has traditionally been described in the time/spatial domain and the intuition behind the entire scheme holds in this domain. It is known that the lifting scheme, as conventionally desc...

We describe several \wavelet transforms" which characterize smoothness spaces and for which the coe cients are obtained by sampling rather than integration. We use them to re-interpret the empirical wavelet transform, i.e. the common practice of applying pyramid lters to samples of a function.

The presence of film grain often imposes the crucial quality choice between film enlargement and speed. In this work we present an automatic technique for reducing the amount of grain on film images. The technique reduces the noise by thresholding the wavelet components of the image with parameterised family of functions obtained with an initial training on a set of images. The training produce...

We developed a general way to create integer wavelet transformations that can be used in lossless (reversible) compression of images with arbitrary size. The method, based on some updating techniques such as lifting and correction, allows us to generate a series of reversible integer transformations which have the similar features with the corresponding biorthogonal wavelet transforms and some ...