1.3k citations · 6.8k across the 44 of their papers we have counts for
25 papers · 1 filter
Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis
Adrien Lagrange, Mathieu Fauvel, Stéphane May +2
Supervised classification and representation learning are two widely used classes of methods to analyze multivariate images. Although complementary, these methods have been scarcel…
Compressive Single-pixel Fourier Transform Imaging using Structured Illumination
Amirafshar Moshtaghpour, José M. Bioucas-Dias, Laurent Jacques
Single Pixel (SP) imaging is now a reality in many applications, e.g., biomedical ultrathin endoscope and fluorescent spectroscopy. In this context, many schemes exist to improve t…
Compressive Hyperspectral Imaging: Fourier Transform Interferometry meets Single Pixel Camera
Amirafshar Moshtaghpour, José M. Bioucas-Dias, Laurent Jacques
This paper introduces a single-pixel HyperSpectral (HS) imaging framework based on Fourier Transform Interferometry (FTI). By combining a space-time coding of the light illuminatio…
Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF). Unlike related models based on Markov Random Fields (MR…
External Patch-Based Image Restoration Using Importance Sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper introduces a new approach to patch-based image restoration based on external datasets and importance sampling. The Minimum Mean Squared Error (MMSE) estimate of the imag…
Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network
Charis Lanaras, José Bioucas-Dias, Silvano Galliani +2
The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resol…
Scene-Adapted Plug-and-Play Algorithm with Guaranteed Convergence: Applications to Data Fusion in Imaging
Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
The recently proposed plug-and-play (PnP) framework allows leveraging recent developments in image denoising to tackle other, more involved, imaging inverse problems. In a PnP meth…
Class-specific image denoising using importance sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we propose a new image denoising method, tailored to specific classes of images, assuming that a dataset of clean images of the same class is available. Similarly to…
Class-specific Poisson denoising by patch-based importance sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we address the problem of recovering images degraded by Poisson noise, where the image is known to belong to a specific class. In the proposed method, a dataset of c…
Scene-adapted plug-and-play algorithm with convergence guarantees
Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
Recent frameworks, such as the so-called plug-and-play, allow us to leverage the developments in image denoising to tackle other, and more involved, problems in image processing. A…
Restoring STM images via Sparse Coding: noise and artifact removal
João P. Oliveira, Ana Bragança, José Bioucas-Dias +4
In this article, we present a denoising algorithm to improve the interpretation and quality of scanning tunneling microscopy (STM) images. Given the high level of self-similarity o…
Image Restoration with Locally Selected Class-Adapted Models
Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
State-of-the-art algorithms for imaging inverse problems (namely deblurring and reconstruction) are typically iterative, involving a denoising operation as one of its steps. Using…
R-FUSE: Robust Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation
Qi Wei, Nicolas Dobigeon, Jean-Yves Tourneret +2
This paper proposes a robust fast multi-band image fusion method to merge a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. Following t…
Multi-Band Image Fusion Based on Spectral Unmixing
Qi Wei, Jose Bioucas-Dias, Nicolas Dobigeon +3
This paper presents a multi-band image fusion algorithm based on unsupervised spectral unmixing for combining a high-spatial low-spectral resolution image and a low-spatial high-sp…
Image Restoration and Reconstruction using Variable Splitting and Class-adapted Image Priors
Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
This paper proposes using a Gaussian mixture model as a prior, for solving two image inverse problems, namely image deblurring and compressive imaging. We capitalize on the fact th…
A Framework for Fast Image Deconvolution with Incomplete Observations
Miguel Simões, Luis B. Almeida, José Bioucas-Dias +1
In image deconvolution problems, the diagonalization of the underlying operators by means of the FFT usually yields very large speedups. When there are incomplete observations (e.g…
Image Classification with Rejection using Contextual Information
Filipe Condessa, José Bioucas-Dias, Carlos Castro +2
We introduce a new supervised algorithm for image classification with rejection using multiscale contextual information. Rejection is desired in image-classification applications t…
Fast Spectral Unmixing based on Dykstra's Alternating Projection
Qi Wei, Jose Bioucas-Dias, Nicolas Dobigeon +1
This paper presents a fast spectral unmixing algorithm based on Dykstra's alternating projection. The proposed algorithm formulates the fully constrained least squares optimization…
Robust hyperspectral image classification with rejection fields
Filipe Condessa, Jose Bioucas-Dias, Jelena Kovacevic
In this paper we present a novel method for robust hyperspectral image classification using context and rejection. Hyperspectral image classification is generally an ill-posed imag…
SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization
Filipe Condessa, Jose Bioucas-Dias, Jelena Kovacevic
We present a supervised hyperspectral image segmentation algorithm based on a convex formulation of a marginal maximum a posteriori segmentation with hidden fields and structure te…
Hyperspectral pansharpening: a review
Laetitia Loncan, Luis B. Almeida, José M. Bioucas-Dias +12
Pansharpening aims at fusing a panchromatic image with a multispectral one, to generate an image with the high spatial resolution of the former and the high spectral resolution of…
Performance measures for classification systems with rejection
Filipe Condessa, Jelena Kovacevic, Jose Bioucas-Dias
Classifiers with rejection are essential in real-world applications where misclassifications and their effects are critical. However, if no problem specific cost function is define…
A convex formulation for hyperspectral image superresolution via subspace-based regularization
Miguel Simões, José Bioucas-Dias, Luis B. Almeida +1
Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low spatial resolution. Conversely, multispectral images (MSIs) usually have low spectral and h…
Hyperspectral and Multispectral Image Fusion based on a Sparse Representation
Qi Wei, José Bioucas-Dias, Nicolas Dobigeon +1
This paper presents a variational based approach to fusing hyperspectral and multispectral images. The fusion process is formulated as an inverse problem whose solution is the targ…