246 citations · 1.1k across the 36 of their papers we have counts for
6 papers · 1 filter
A Bayesian approach to denoising of single-photon binary images
Yoann Altmann, Reuben Aspden, Miles Padgett +1
This paper discusses new methods for processing images in the photon-limited regime where the number of photons per pixel is binary. We present a new Bayesian denoising method for…
Robust Linear Spectral Unmixing using Anomaly Detection
Yoann Altmann, Steve McLaughlin, Alfred Hero
This paper presents a Bayesian algorithm for linear spectral unmixing of hyperspectral images that accounts for anomalies present in the data. The model proposed assumes that the p…
Spectral unmixing of Multispectral Lidar signals
Yoann Altmann, Andrew Wallace, Steve McLaughlin
In this paper, we present a Bayesian approach for spectral unmixing of multispectral Lidar (MSL) data associated with surface reflection from targeted surfaces composed of several…
Bayesian nonlinear hyperspectral unmixing with spatial residual component analysis
Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin
This paper presents a new Bayesian model and algorithm for nonlinear unmixing of hyperspectral images. The model proposed represents the pixel reflectances as linear combinations o…
Residual component analysis of hyperspectral images -- Application to joint nonlinear unmixing and nonlinearity detection
Yoann Altmann, Nicolas Dobigeon, Steve McLaughlin +1
This paper presents a nonlinear mixing model for joint hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are linear co…
Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm
Yoann Altmann, Nicolas Dobigeon, Jean-Yves Tourneret
This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are post-nonlinear functions of unknown pure s…