Now showing items 1-5 of 5
Multiscale Geometric Image Processing
Since their introduction a little more than 10 years ago, wavelets have revolutionized image processing. Wavelet based algorithms define the state-of-the-art for applications including image coding (JPEG2000), restoration, ...
Multiscale Image Segmentation Using Joint Texture and Shape Analysis
We develop a general framework to simultaneously exploit texture and shape characterization in multiscale image segmentation. By posing multiscale segmentation as a model selection problem, we invoke the powerful framework ...
Multiscale Edge Grammars for Complex Wavelet Transforms
Wavelet domain algorithms have risen to the forefront of image processing. The power of these algorithms is derived from the fact that the wavelet transform restructures the image in a way that makes statistical modeling ...
Multiscale Wedgelet Image Analysis: Fast Decompositions and Modeling
The most perceptually important features in images are geometrical, the most prevalent being the smooth contours ("edges") that separate different homogeneous regions and delineate distinct objects. Although wavelet based ...
Bayesian Tree-Structured Image Modeling using Wavelet-domain Hidden Markov Models
Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet ...