We propose a new wavelet compression algorithm based on the rate-distortion optimization for densely sampled triangular meshes. Exploiting the normal remesher of Guskov et al., th...
We present an algorithm for compressing 2D vector fields that preserves topology. Our approach is to simplify the given data set using constrained clustering. We employ different...
Suresh K. Lodha, Jose C. Renteria, Krishna M. Rosk...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
Abstract--This paper describes performance bounds for compressed sensing (CS) where the underlying sparse or compressible (sparsely approximable) signal is a vector of nonnegative ...
Maxim Raginsky, Rebecca Willett, Zachary T. Harman...
We study the detection performance of large scale sensor networks, configured as trees with bounded height, in which information is progressively compressed as it moves towards th...