On Space-spectrum Uncertainty Analysis for Coded Aperture Systems

TL;DR

This paper introduces the concept of space-spectrum uncertainty in spectrally programmable cameras, demonstrating a fundamental trade-off between spatial resolution and spectral resolution due to Fourier relationships, validated through experiments.

Contribution

It presents the first analysis of space-spectrum uncertainty, establishing a lower bound on the product of spatial and spectral resolutions in such systems.

Findings

High spatial resolution limits spectral resolution and vice versa.

A lower bound on the product of spatial and spectral standard deviations is derived.

Experimental validation confirms the theoretical trade-off.

Abstract

We introduce and analyze the concept of space-spectrum uncertainty for certain commonly-used designs for spectrally programmable cameras. Our key finding states that, it is impossible to simultaneously capture high-resolution spatial images while programming the spectrum at high resolution. This phenomenon arises due to a Fourier relationship between the aperture used for obtaining spectrum and its corresponding diffraction blur in the (spatial) image. We show that the product of spatial and spectral standard deviations is lower bounded by {\lambda}/4{\pi}{\nu_0} femto square-meters, where {\nu_0} is the density of groves in the diffraction grating and {\lambda} is the wavelength of light. Experiments with a lab prototype for simultaneously measuring spectrum and image validate our findings and its implication for spectral filtering.