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HYPERSPECTRAL IMAGE DENOISING USING A NONLOCAL SPECTRAL SPATIAL PRINCIPAL COMPONENT ANALYSIS
Hyperspectral Images Noise Reduction Nonlocal Similarity Spectral Spatial Information Principal Component Analysis
2018/5/14
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classi...
Ideal Denoising in an orthonormal basis chosen from a library of bases
Wavelet Packets Cosine Packets weak-` p spaces
2015/8/20
Suppose we have observations yi = si +zi, i = 1; :::; n, where (si) is signal and (zi)
is i.i.d. Gaussian white noise. Suppose we have available a library L of orthogonal
bases, such as the Wavelet ...
The Curvelet Transform for Image Denoising
Radon Transform Wavelets Ridgelets Curvelets FFT FWT Discrete Wavelet Transform Thresholding Rules Filtering
2015/6/17
We describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform [3] and the curvelet transform [7, 6]. Our implementations offer exact reconstruction...
Compressed Sensing for Denoising in Adaptive System Identification
Sparse system identification compressed sensing reconstruction algorithm random filter least mean square
2012/4/23
We propose a new technique for adaptive identification of sparse systems based on the compressed sensing (CS) theory. We manipulate the transmitted pilot (input signal) and the received signal such th...
Atomic norm denoising with applications to line spectral estimation
Atomic norm line spectral estimation Information Theory
2012/4/18
The sub-Nyquist estimation of line spectra is a classical problem in signal processing, but currently popular subspace-based techniques have few guarantees in the presence of noise and rely on a prior...
Image denoising by regularization on characteristic graphs
Image Restoration Denoising, Graph Regularization
2010/9/27
This paper introduces improvements to a now classical family of image denoising methods through rather minimal changes to the way derivatives are computed. In particular, we ask, and answer, the quest...
Denoising gravity and geomagnetic signals from Etna volcano (Italy) using multivariate methods
geomagnetic signals Etna volcano multivariate methods
2009/11/2
Multivariate methods were applied to denoise the gravity and geomagnetic signals continuously recorded by the permanent monitoring networks on the Etna volcano. Gravity and geomagnetic signals observe...
Information denoising and quantization by diffusion reaction model
signal restoration reaction-diffusion model partial differential equations numerical approximation
2009/1/7
We present a new diffusion reaction model for signal denoising
and quantization. We first discuss on classical quantization methods
and present the most popular denoising models. Then we construct o...