Spatial spectroscopy for high resolution imaging

Abstract

Quantum estimation theory provides bounds for the precision in the estimation of a set of parameters that characterize a system. Two questions naturally arise: Is any of these bounds tight? And if this is the case, what type of measurements can attain such a limit? In this work we show that for phase objects, it is possible to find a tight resolution bound. Moreover one can find a set of spatial modes whose detection provides an optimal estimation of the complete set of parameters for which we propose a homodyne detection scheme. We call this method spatial spectroscopy since it mimics in the spatial domain what conventional spectroscopy methods do in the frequency domain employing many frequencies (hyperspectral imaging).

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

“…When the spatial resolution of the images reaches the meter level, most of the surface targets such as tree, car, road, and house will appear precisely on the image. With the outstanding high spatial resolution, high-definition remote sensing images can realize fine earth observation and obtain geometric structure, texture size, spatial layout, and other characteristic information of feature targets, with good conditions and foundation for interpretation and analysis (Villegas and Torres 2020). However, how to make best use of the potential of more accurate spatial resolution Therefore, researchers often use a basic quality parameter of remote sensing data to uniquely determine the application potential of high-spatial-resolution remote sense datasets (Villegas and Torres 2020).…”