A comprehensive survey on impulse and Gaussian denoising filters for digital images
M Mafi, H Martin, M Cabrerizo, J Andrian, A Barreto… - Signal Processing, 2019 - Elsevier
This review article provides a comprehensive survey on state-of-the-art impulse and
Gaussian denoising filters applied to images and summarizes the progress that has been …
Gaussian denoising filters applied to images and summarizes the progress that has been …
Hidden markov processes
An overview of statistical and information-theoretic aspects of hidden Markov processes
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …
Automatic speech recognition: a survey
Recently great strides have been made in the field of automatic speech recognition (ASR) by
using various deep learning techniques. In this study, we present a thorough comparison …
using various deep learning techniques. In this study, we present a thorough comparison …
A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction
Purpose Due to the potential risk of inducing cancer, radiation exposure by X‐ray CT
devices should be reduced for routine patient scanning. However, in low‐dose X‐ray CT …
devices should be reduced for routine patient scanning. However, in low‐dose X‐ray CT …
A deep learning approach to structured signal recovery
In this paper, we develop a new framework for sensing and recovering structured signals. In
contrast to compressive sensing (CS) systems that employ linear measurements, sparse …
contrast to compressive sensing (CS) systems that employ linear measurements, sparse …
EMD-based temporal and spectral features for the classification of EEG signals using supervised learning
This paper presents a novel method for feature extraction from electroencephalogram (EEG)
signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the …
signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the …
Springer series in statistics
The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Statistics of real-world hyperspectral images
A Chakrabarti, T Zickler - CVPR 2011, 2011 - ieeexplore.ieee.org
Hyperspectral images provide higher spectral resolution than typical RGB images by
including per-pixel irradiance measurements in a number of narrow bands of wavelength in …
including per-pixel irradiance measurements in a number of narrow bands of wavelength in …
Adaptive wavelet thresholding for image denoising and compression
The first part of this paper proposes an adaptive, data-driven threshold for image denoising
via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the …
via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the …