Results 131 to 140 of about 224 (152)
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Global semantic classification of scenes using ridgelet transform

SPIE Proceedings, 2004
In recent years, new harmonic analysis tools providing sparse representation in high dimension space have been proposed. In particular, ridgelets and curvelets bases are similar to the sparse components of naturally occurring image data derived empirically by computational neuroscience researchers.
Samuel Foucher   +2 more
openaire   +1 more source

Color Image Compression Using Wavelet and Ridgelet Transform

2010 Seventh International Conference on Information Technology: New Generations, 2010
Image Compression is a widely explored research area. Many compression standards are existing. But still there is a scope for higher compression with quality reconstruction. The introduction of wavelets gave a different dimension to the compression. This paper aims at exploration of use of Ridgelet Transform and Wavelet Transform for color images.
Madhuri Satish Joshi   +2 more
openaire   +2 more sources

A Continuous Transform for Localized Ridgelets

2023 International Conference on Sampling Theory and Applications (SampTA), 2023
Joseph Shenouda   +2 more
openaire   +1 more source

Pseudo Ridgelet Transform for Image Denoising

2009 WASE International Conference on Information Engineering, 2009
Wavelet transforms have been successfully used in many scientific fields such as image denoising. Ridgelets is a new system of representations, which deals effectively with line singularities in 2-D. However, the discrete version of the ridgelet transform would result in either redundancy or non-reconstruction.
openaire   +1 more source

Generalized Finite Continuous Ridgelet Transform

2022
Nitu Gupta, V. R. Lakshmi Gorty
openaire   +1 more source

Polar linear canonical ridgelet transform

Digital Signal Processing
Rong-Qian Linghu, Bing-Zhao Li
openaire   +1 more source

On the double windowed ridgelet transform and its inverse

Integral Transforms and Special Functions, 2020
Tamotu Kinoshita
exaly  

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