· HDSP Group · Journal · 2 min read
Welcome to HDSP!
An introduction to the High Dimensional Signal Processing Research Group and the scientific challenges that motivate its work.
In the last 40 years, the developments in sensing, analysis, and processing of digital signals have grown considerably. Recent advances in signal processing algorithms and digital signal processors have enabled diverse digital applications such as audio enhancement, digital image processing, digital image sensing and visualization, Fourier analysis, and many others. In the last 10 years, the digital field has grown almost exponentially, and most importantly, the digital domain has explored new areas of application. Areas such as random matrix analysis, optimization, and statistical signal processing have been fused to create a new era of signal processing algorithms based on compressed sensing of sparse signals. Surprisingly, this new era of compressed sensing theory has challenged the well-known Nyquist theory. As a result, new applications of signal processing have emerged in new areas. In microscopy, for instance, new compressed algorithms make it possible to overcome the diffraction limit of lenses by using super-resolution techniques. It is now possible to observe super-resolved microscopy images. Radar, holography, and tomography applications use much fewer samples than those required by the Nyquist limit. Three-dimensional hyperspectral images can be sensed on the fly by using two-dimensional snapshots.
In the same direction, researchers and society have started to demand high-quality signals such that RGB images are replaced by multispectral images, high-resolution images reach orders of terapixels, traditional audio signals are replaced by high-quality audio signals, and classic two-dimensional TV visualization is replaced by three-dimensional TV. A challenging problem has emerged: how do we sense, analyze, process, and compute the tremendous amount of data involved in high-dimensional signals? Professor Henry Arguello studies this problem through applications such as statistical signal processing, super-resolution, inverse problems, optical imaging, video processing, hyperspectral imaging, and compressive sensing.
Professor Henry works with researchers from numerous disciplines including electrical engineering, electronics, computer science, physics, chemistry, and chemical engineering. His motivation is to move beyond the traditional Digital Signal Processing (DSP) area toward a more powerful field that integrates computation, statistics, matrix analysis, compression, sensing, optimization, and algorithms. This field is HDSP.
