Results 151 to 160 of about 4,538 (213)

A Breast Cancer Image Classification Algorithm with 2c Multiclass Support Vector Machine. [PDF]

J Healthc Eng, 2023
Wajeed MA, Tiwari S, Gupta R, Ahmad AJ, Agarwal S, Jamal SS, Hinga SK.   +6 more
europepmc   +1 more source

A Shearlet-TV Regularization Approach for Image Denoising in the ADMM Framework

, 2017
Xingguo Liu, Yingpin Chen, Zhenming Peng, Juan Wu, W Li, Q Li, M Elad, M Figueiredo, C Deng, W Tian, D Donoho, G Kutyniok, T Sauer, K Guo, D Labate, S Boyd, N Parikh, A Beck, M Teboulle   +18 more
openalex   +1 more source

Fusion technique for SAR and Gray Visible Image based on Hidden Markov Model in Non-subsample Shearlet Transform Domain [PDF]

, 2015
Jian Liu, Yingjie Lei, Yaqiong Xing, Chuanguo Lu   +3 more
openalex   +1 more source

A multi-scale pyramid residual weight network for medical image fusion. [PDF]

Quant Imaging Med Surg
Liu Y, Zhang S, Tang Y, Zhao X, He ZX.
europepmc   +1 more source

First arrival time picking for microseismic data based on shearlet transform [PDF]

, 2017
Yao Cheng, Yue Li, Chao Zhang
openalex   +1 more source

Comparing Undecimated Wavelet, Nonsubsampled Contourlet and Shearlet for Sar Images Despeckling

Majlesi Journal of Electrical Engineering
Synthetic Aperture Radar (SAR) images suffer of multiplicative speckle noise, which damages the radiometric resolution of SAR images and makes the data interpretation difficult.
Saeed Jafari, Sedigheh Ghofrani, M. Sheikhan   +2 more
doaj  

Compressive Learning for the Classification and Reconstruction of Synthetic Aperture Radar Data. [PDF]

Sensors (Basel)
Keymasi M, Ghozatlou O, Heredia Conde M, Datcu M.   +3 more
europepmc   +1 more source

ECFuse: Edge-Consistent and Correlation-Driven Fusion Framework for Infrared and Visible Image Fusion. [PDF]

Sensors (Basel), 2023
Chen H, Deng L, Zhu L, Dong M.
europepmc   +1 more source

Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features. [PDF]

Sci Rep
Pugazharasi K, Sakthivel K.
europepmc   +1 more source

Blind deconvolution using shearlet -tv regularization

, 2019
In this article we propose two minimization models for blind deconvolution. In the first model, we use shearlet transform as a regularization term for recovering image. Also total variation method is used as a regularization term for point spread function(PSF). To speed up the process, Fast ADMM approach is exploited.
MOUSAVİ, Z., MOKHTARİ, R., LAKESTANİ, M.   +2 more
openaire   +2 more sources