Rick Chartrand
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View article: NONCONVEX REGULARIZATION FOR IMAGE SEGMENTATION
NONCONVEX REGULARIZATION FOR IMAGE SEGMENTATION Open
- We propose a new method for image segmentation based on a variational regularization algorithm for image denoising. We modify the Rudin-Osher-Fatemi (ROF) model in [1] by minimizing the p L-norm of the gradient, where p> 0 is very sma…
View article: Fast algorithms for nonconvex compression sensing: MRI reconstruction from very few data
Fast algorithms for nonconvex compression sensing: MRI reconstruction from very few data Open
Compressive sensing is the reconstruction of sparse images or signals from very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can allow reconstruction from many fewer k-space samples, thereb…
View article: Image fusion using sparse overcomplete feature dictionaries
Image fusion using sparse overcomplete feature dictionaries Open
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset a…
View article: BUDD: Multi-modal Bayesian Updating Deforestation Detections
BUDD: Multi-modal Bayesian Updating Deforestation Detections Open
The global phenomenon of forest degradation is a pressing issue with severe implications for climate stability and biodiversity protection. In this work we generate Bayesian updating deforestation detection (BUDD) algorithms by incorporati…
View article: Data-Intensive Supercomputing in the Cloud: Global Analytics for Satellite Imagery
Data-Intensive Supercomputing in the Cloud: Global Analytics for Satellite Imagery Open
We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in high-performance computing, we draw parallels between the early days of c…
View article: Wavelet-Compressed Representation of Landscapes for Hydrologic and Geomorphologic Applications
Wavelet-Compressed Representation of Landscapes for Hydrologic and Geomorphologic Applications Open
The availability of high-resolution digital elevation data (submeter resolution) from LiDAR has increased dramatically over the past few years. As a result, the efficient storage and transmission of those large data sets and their use for …