Results 31 to 40 of about 258 (126)

Improved Reconstruction of MR Scanned Images by Using a Dictionary Learning Scheme

Sensors, 2019
The application of compressed sensing (CS) to biomedical imaging is sensational since it permits a rationally accurate reconstruction of images by exploiting the image sparsity.
Shahid Ikram, Jawad Ali Shah, Syed Zubair, Ijaz Mansoor Qureshi, Muhammad Bilal   +4 more
doaj   +1 more source

An Efficient Skin Cancer Diagnostic System Using Bendlet Transform and Support Vector Machine

Anais da Academia Brasileira de Ciências
Skin is the outermost and largest organ of the human body that protects us from the external agents. Among the various types of diseases affecting the skin, melanoma (skin cancer) is the most dangerous and deadliest disease.
POOVIZHI S, GANESH BABU TR
doaj   +1 more source

Pyramidal directional filter banks and curvelets [PDF]

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002
A flexible multiscale and directional representation for images is proposed. The scheme combines directional filter banks with the Laplacian pyramid to provide a sparse representation for two-dimensional piecewise smooth signals resembling images. The underlying expansion is a frame and can be designed to be a tight frame.
Minh N. Do, Martin Vetterli
openaire   +1 more source

Data-Proximal Complementary ℓ¹-TV Reconstruction for Limited Data Computed Tomography

Mathematics
In a number of tomographic applications, data cannot be fully acquired, resulting in severely underdetermined image reconstruction. Conventional methods in such cases lead to reconstructions with significant artifacts.
Simon Göppel, Jürgen Frikel, Markus Haltmeier   +2 more
doaj   +1 more source

Seismic Amplitude Recovery with Curvelets

, 2007
A non-linear singularity-preserving solution to the least-squares seismic imaging problem with sparseness and continuity constraints is proposed. The applied formalism explores curvelets as a directional frame that, by their sparsity on the image, and their invariance under the imaging operators, allows for a stable recovery of the amplitudes.
Moghaddam, P.P., Herrmann, F.J., Stolk, C.C.   +2 more
openaire   +2 more sources

Curvelet transform for Boehmians

Arab Journal of Mathematical Sciences, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Subash Moorthy Rajendran, Roopkumar Rajakumar   +1 more
openaire   +2 more sources

Quantum algorithms using the curvelet transform [PDF]

Proceedings of the forty-first annual ACM symposium on Theory of computing, 2009
64 pages, 4 figures; improved algorithm and lower bound for finding the center of a radial function; revised presentation; to appear in STOC ...
openaire   +3 more sources

Face Recognition Using Curvelet Transform

, 2010
This paper presents a new method for the problem of human face recognition from still images. This is based on a multiresolution analysis tool called Digital Curvelet Transform. Curvelet transform has better directional and edge representation abilities than wavelets.
Hana Hejazi, Mohammed Alhanjouri
openaire   +2 more sources

Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney. [PDF]

Sci Data, 2023
Kuo W, Rossinelli D, Schulz G, Wenger RH, Hieber S, Müller B, Kurtcuoglu V.   +6 more
europepmc   +1 more source

Curvelet Transform-Based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy. [PDF]

IEEE Trans Med Imaging, 2022
You Q, Trzasko JD, Lowerison MR, Chen X, Dong Z, ChandraSekaran NV, Llano DA, Chen S, Song P.   +8 more
europepmc   +1 more source