Ma, J.,
Plonka, G.,
Combined Curvelet Shrinkage and Nonlinear Anisotropic Diffusion,
IP(16), No. 9, September 2007, pp. 2198-2206.
IEEE DOI
0709
BibRef
Jiang, L.L.[Ling-Ling],
Feng, X.C.[Xiang-Chu],
Yin, H.Q.[Hai-Qing],
Variational Image Restoration and Decomposition with Curvelet Shrinkage,
JMIV(30), No. 2, February 2008, pp. 125-132.
Springer DOI
0801
BibRef
Ma, J.,
Plonka, G.,
The Curvelet Transform,
SPMag(27), No. 2, 2010, pp. 118-133.
IEEE DOI
1003
BibRef
Storath, M.[Martin],
Directional Multiscale Amplitude and Phase Decomposition by the
Monogenic Curvelet Transform,
SIIMS(4), No. 1, 2011, pp. 57-78.
DOI Link
BibRef
1100
Earlier:
The monogenic curvelet transform,
ICIP10(353-356).
IEEE DOI
1009
curvelet transform, analytic signal, monogenic signal, Hilbert
transform, Riesz transform, directional wavelet transform
BibRef
Cui, H.[Hua],
Yan, G.B.[Ga-Beng],
Song, H.S.[Huan-Sheng],
A novel curvelet thresholding denoising method based on chi-squared
distribution,
SIViP(9), No. 2, February 2015, pp. 491-498.
WWW Link.
1503
BibRef
Aghazadeh, N.[Nasser],
Akbarifard, F.[Farideh],
Cigaroudy, L.S.[Ladan Sharafyan],
A restoration-segmentation algorithm based on flexible Arnoldi-Tikhonov
method and Curvelet denoising,
SIViP(10), No. 5, May 2016, pp. 935-942.
Springer DOI
1608
BibRef
Balci, H.[Hasan],
Güdükbay, U.[Ugur],
Sun position estimation and tracking for virtual object placement in
time-lapse videos,
SIViP(11), No. 5, July 2017, pp. 817-824.
WWW Link.
1706
BibRef
Qiao, T.,
Ren, J.,
Wang, Z.,
Zabalza, J.,
Sun, M.,
Zhao, H.,
Li, S.,
Benediktsson, J.A.,
Dai, Q.,
Marshall, S.,
Effective Denoising and Classification of Hyperspectral Images Using
Curvelet Transform and Singular Spectrum Analysis,
GeoRS(55), No. 1, January 2017, pp. 119-133.
IEEE DOI
1701
data acquisition
BibRef
Al-Marzouqi, H.[Hasan],
Al Regib, G.[Ghassan],
Curvelet transform with learning-based tiling,
SP:IC(53), No. 1, 2017, pp. 24-39.
Elsevier DOI
1703
Directional transforms
BibRef
Wang, X.K.[Xiao-Kai],
Chen, W.C.[Wen-Chao],
Gao, J.H.[Jing-Huai],
Wang, C.[Chao],
Hybrid image denoising method based on non-subsampled contourlet
transform and bandelet transform,
IET-IPR(12), No. 5, May 2018, pp. 778-784.
DOI Link
1804
BibRef
Panigrahi, S.K.[Susant Kumar],
Gupta, S.[Supratim],
Sahu, P.K.[Prasanna K.],
Curvelet-based multiscale denoising using non-local means and guided
image filter,
IET-IPR(12), No. 6, June 2018, pp. 909-918.
DOI Link
1805
BibRef
Kadri, O.[Oussama],
Baarir, Z.E.[Zine-Eddine],
Schaefer, G.[Gerald],
Power shrinkage-curvelet domain image denoising using a new
scale-dependent shrinkage function,
SIViP(13), No. 7, October 2019, pp. 1347-1355.
WWW Link.
1911
BibRef
Li, Y.[Ying],
Ning, H.J.[Hui-Jun],
Zhang, Y.N.[Yan-Ning],
Feng, D.D.[David Dagan],
Nonlinear curvelet diffusion for noisy image enhancement,
ICIP11(2557-2560).
IEEE DOI
1201
BibRef
Wang, X.C.[Xin-Chun],
Hong, M.[Ming],
Yang, Y.F.[Yong-Feng],
Images de-noising with Mapshrink estimate and dual-threshold in
Curvelet Domain,
IASP10(304-308).
IEEE DOI
1004
BibRef
Li, D.[Dan],
Qian, J.S.[Jian-Sheng],
Research on image denoising new method based on curvelet transform,
IASP10(202-205).
IEEE DOI
1004
BibRef
Crosby, F.[Frank],
Curvelet decomposition for detection of cylindrical targets,
ICIP08(2832-2835).
IEEE DOI
0810
BibRef
Alecu, A.[Alin],
Munteanu, A.[Adrian],
Piurica, A.[Aleksandra],
Cornelis, J.P.H.[Jan P.H.],
Schelkens, P.[Peter],
Analysis of the Statistical Dependencies in the Curvelet Domain and
Applications in Image Compression,
ACIVS07(1061-1071).
Springer DOI
0708
BibRef
Alecu, A.,
Munteanu, A.,
Pizurica, A.[Aleksandra],
Philips, W.[Wilfried],
Cornelis, J.P.H.,
Schelkens, P.,
Information-Theoretic Analysis of Dependencies Between Curvelet
Coefficients,
ICIP06(1617-1620).
IEEE DOI
0610
BibRef
Abrial, P.,
Starck, J.L.,
Moudden, Y.,
Nguyen, M.,
Curvelet Transform on the Sphere,
ICIP05(I: 737-740).
IEEE DOI
0512
See also Undecimated Wavelet Decomposition and its Reconstruction, The.
BibRef
Do, M.,
Vetterli, M.,
Pyramidal Directional Filter Banks and Curvelets,
ICIP01(III: 158-161).
IEEE DOI
0108
BibRef
Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Fractal Representations, Fractal Dimension .