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» Lossy Compression of Bilevel Images Based on Markov Random F...
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81
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ICIP
2007
IEEE
15 years 3 months ago
Lossy Compression of Bilevel Images Based on Markov Random Fields
A new method for lossy compression of bilevel images based on Markov random fields (MRFs) is proposed. It preserves key structural information about the image, and then reconstru...
Matthew G. Reyes, Xiaonan Zhao, David L. Neuhoff, ...
3DOR
2008
14 years 12 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
78
Voted
ICIP
1994
IEEE
15 years 11 months ago
A Tree Structured Bayesian Scalar Quantizer for Wavelet Based Image Compression
ABSTRACT the pyramid. Recently, a number of promising quanMultiresolution imagedecompositions (e. g., wavelets), in conjunction with a variety of quantization schemes, have been sh...
Birsen Yazici, Mary L. Comer, Rangasami L. Kashyap...
118
Voted
MM
2006
ACM
221views Multimedia» more  MM 2006»
15 years 3 months ago
Video object segmentation by motion-based sequential feature clustering
Segmentation of video foreground objects from background has many important applications, such as human computer interaction, video compression, multimedia content editing and man...
Mei Han, Wei Xu, Yihong Gong
CAIP
2009
Springer
202views Image Analysis» more  CAIP 2009»
14 years 7 months ago
Near-Regular Texture Synthesis
This paper describes a method for seamless enlargement or editing of difficult colour textures containing simultaneously both regular periodic and stochastic components. Such textu...
Michal Haindl, Martin Hatka