Lossy compression of hyperspectral and ultraspectral images is traditionally performed using 3D transform coding. This approach yields good performance, but its complexity and mem...
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...
Motion estimation methods based on differential techniques proved to be very useful in the context of video analysis, but have a limited employment in classical video compression ...
Minimum Spanning Tree (MST) is one of the most studied combinatorial problems with practical applications in VLSI layout, wireless communication, and distributed networks, recent ...