نتایج جستجو برای: shearlet group

تعداد نتایج: 979538  

Journal: :Sampling Theory, Signal Processing, and Data Analysis 2011

Journal: :International Journal of Hybrid Information Technology 2016

Journal: :International Journal of Computer Applications 2015

2017
Jackie Ma Maximilian März

We propose an algorithmic framework based on ADMM/split Bregman that combines a multilevel adapted, iterative reweighting strategy and a second total generalized variation regularizer. The level adapted reweighting strategy is a combination of reweighted `-minimization and additional compensation factors for a uniform treatment of the sparsity structure across all levels. Classical multilscale ...

Journal: :Journal of Signal and Information Processing 2016

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تبریز 1382

‏‎in this research,the authors conducted a study comparing two groups of male and female english language learners studying in a elt institute,in terms of their performance on their achievement test including listening comprehension,vocabulary,grammar,and reading comprehension and found no significant difference between the group except in listening comprehension part of the test in which the f...

Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising a...

2010
Holger Rauhut Tino Ullrich

Coorbit space theory is an abstract approach to function spaces and their atomic decompositions. The original theory developed by Feichtinger and Gröchenig in the late 1980ies heavily uses integrable representations of locally compact groups. Their theory covers, in particular, homogeneous Besov-Lizorkin-Triebel spaces, modulation spaces, Bergman spaces and the recent shearlet spaces. However, ...

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