基于超瑞利散斑的深度学习高光谱图像重建

Deep Learning Enabled Real Time Speckle Recognition and Hyperspectral Imaging using a Multimode Fiber Array

We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral transmission matrix. Optimized neural networks trained on these datasets achieve reliable reconstruction of both discrete and continuous spectra from a monochromatic camera image. Deep learning is compared to analytical inversion methods as well as to a compressive sensing algorithm and shows favourable characteristics both in the oversampling and in the sparse u…

基于结构散斑照明的亚瑞利鬼成像

Sub-Rayleigh Ghost Imaging via Structured Speckle Illumination

本文提出利用正弦及伪调制结构散斑照明突破瑞利分辨率极限，实现空间分辨率提升2倍以上的鬼成像，并验证其可与伪逆鬼成像等亚瑞利方案结合以进一步增强分辨率。

Polarized hyperspectral imaging with single fiber bundle via incoherent light transmission matrix approach

The scattering of multispectral incoherent light is a common and unfavorable signal scrambling in natural scenes. However, the blurred light spot due to scattering still holds lots of information remaining to be explored. Former methods failed to recover the polarized hyperspectral information from scattered incoherent light or relied on additional dispersion elements. Here we put forward the transmission matrix (TM) approach for extended objects under incoherent illumination by speculating the unknown TM through experimentally calibrated or digitally emulated ways. Employing a fiber bundle as…

Spectral ghost imaging camera with super-Rayleigh modulator

A spectral camera based on ghost imaging via sparsity constraints (GISC) acquires a spectral data-cube (x; y; λ) through a single exposure. The noise immunity of the system is one of the important factors affecting the quality of the reconstructed images, especially at low sampling rates. Tailoring the intensity to generate super-Rayleigh speckle patterns which have superior noise immunity may offer an effective route to promote the imaging quality of GISC spectral camera. According to the structure of GISC spectral camera, we proposed a universal method for generating super-Rayleigh speckle p…

Snapshot fiber spectral imaging using speckle correlations and compressive sensing

Snapshot spectral imaging is rapidly gaining interest for remote sensing applications. Acquiring spatial and spectral data within one image promotes fast measurement times, and reduces the need for stabilized scanning imaging systems. Many current snapshot technologies, which rely on gratings or prisms to characterize wavelength information, are difficult to reduce in size for portable hyperspectral imaging. Here, we show that a multicore multimode fiber can be used as a compact spectral imager with sub-nanometer resolution, by encoding spectral information within a monochrome CMOS camera. We …

Breaking Rayleigh's Criterion via Discernibility in High-Dimensional Light-Field Space with Snapshot Ghost Imaging

By encoding the high-dimensional light-field imaging information into a detectable two-dimensional speckle plane, ghost imaging camera via sparsity constraints (GISC camera) can directly catch the high-dimensional light-field imaging information with only one snapshot. This makes it worth to revisit the spatial resolution limit of this optical imaging system. In this paper we show both theoretically and experimentally that, while the resolution in high-dimensional light-field space is still limited by diffraction, the statistical spatial resolution of GISC camera can be greatly improved compar…