Affiliation:
1. Key Laboratory of Optoelectronic Devices and Detection Technology, School of Physics, Liaoning University, Shenyang 110036, China
Abstract
Single-pixel hyperspectral imaging (HSI) has received a lot of attention in recent years due to its advantages of high sensitivity, wide spectral ranges, low cost, and small sizes. In this article, we perform a single-pixel HSI experiment based on an untrained convolutional neural network (CNN) at an ultralow sampling rate, where the high-quality retrieved images of the target objects can be achieved by every visible wavelength of a light source from 432 nm to 680 nm. Specifically, we integrate the imaging physical model of single-pixel HSI into a randomly initialized CNN, which allows the images to be reconstructed by relying solely on the interaction between the imaging physical process and the neural network without pre-training the neural network.
Funder
National Key Research and Development Program of China
Subject
Radiology, Nuclear Medicine and imaging,Instrumentation,Atomic and Molecular Physics, and Optics
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