Terrain reconstruction from Chang'e-3 PCAM images

The existing terrain models that describe the local lunar surface have limited resolution and accuracy, which can hardly meet the needs of rover navigation,positioning and geological analysis. China launched the lunar probe Chang＇e-3 in December, 2013. Chang＇e-3 encompassed a lander and a lunar rover called ＂Yutu＂（Jade Rabbit）. A set of panoramic cameras were installed on the rover mast. After acquiring panoramic images of four sites that were explored, the terrain models of the local lunar surface with resolution of 0.02 m were reconstructed. Compared with other data sources, the models derived from Chang＇e-3 data were clear and accurate enough that they could be used to plan the route of Yutu.

Principle of subtraction ghost imaging in scattering medium

Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost imaging.The disturbance is usually eliminated by the method of pre-compensation.We deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target object.The effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical results.Our research may provide a new idea of ghost imaging in harsh environment.

Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP_(3)model

Fluorescence molecular tomography(FMT)allows the detection and quantification of various biological processes in small animals in vrivo,which expands the horizons of pre clinical rescarch and drug development.Eficient three dimensional(3D)reconstruction algorithm is the key to accurate localization and quant ification of fAuorescent target in FMT.In this paper,3D recon-struction of FMT is regarded as a sparse signal recovery problem and the compressive sampling matching pursuit(CoSaMP)algorithm is adopted to obtain greedy recovery of fuorescent sig-nals.Moreover,to reduce the modeling error,the simplified spherical harmonics approximation to the radiative transfer equation(RTE),more specifically SP_(3),is utilized to describe light prop-agation in biological tissues.The performance of the proposed reconstruction method is thor-oughly evaluated by simulations on a 3D digital mouse model by comparing it with three representative greedy methods including orthogonal matching pursuit(OMP),stagewise OMP(StOMP),and regularized OMP(ROMP).The CoSaMP combined with SP_(3)shows an im-provement in reconstruction accuracy and exhibits distinct advantages over the comparative algorithms in multiple targets resolving.Stability analysis suggests that CoSaMP is robust to noise and performs stably with reduction of measurements.The feasibility and reoonstruction accuracy of the proposed method are further validated by phantom experimental data.

Handheld diffuse optical breast scanner probe for cross-sectional imaging of breast tissue

Diffuse optical spectroscopy is a relatively new,noninvasive and nonionizing technique for breast cancer diagnosis.In the present study,we have introduced a novel handheld diffuse optical breast scan(DOB-Scan)probe to measure optical properties of the breast in vivo and create functional and compositional images of the tissue.In addition,the probe gives more information about breast tissue's constituents,which helps distinguish a healthy and cancerous tissue.Two symmetrical light sources,each including four different wavelengths,are used to illuminate the breast tissue.A high-resolution linear array detector measures the intensity of the back-scattered photons at different radial destinations from the illumination sources on the surface of the breast tissue,and a unique image reconstruction algorithm is used to create four cross-sectional images for four different wavelengths.Different fromfiber optic-based illumination techniques,the proposed method in this paper integrates multi-wavelength light-emitting diodes to act as pencil beam sources into a scattering medium like breast tissue.This unique design and its compact structure reduce the complexity,size and cost of a potential probe.Although the introduced technique miniaturizes the probe,this study points to the reliability of this technique in the phantom study and clinical breast imaging.We have received ethical approval to test the DOB-Scan probe on patients and we are currently testing the DOB-Scan probe on subjects who are diagnosed with breast cancer.

The Matrix Transform for Reconstruction on Finite-Element-Based Photoacoustic Tomography

Numerical Finite-element method (FEM) based algorithms have been widely applied for the reconstruction of the photoacoustic image. As compared with the traditional analytic methods, the FEM based methods can be easily used to deal with problems with irregularly shaped imaging domain. However, the FEM based algorithms are usually computationally intensive because repeated manipulations of matrices with larger size are needed during the reconstruction process. To tackle such a problem, a novel method is proposed for reducing the size of the matrix to be inversed during the reconstruction process and hence speed up the inverse reconstruction without any sacrifice of the reconstruction accuracy.

Terahertz two-pixel imaging based on complementary compressive sensing

A compact terahertz（THz） imaging system based on complementary compressive sensing has been proposed using two single-pixel detectors. By using a mechanical spatial light modulator, sampling in the transmission and reflection orientations was achieved simultaneously, which allows imaging with negative mask values. The improvement of THz image quality and anti-noise performance has been verified experimentally compared with the traditional reconstructed image, and is in good agreement with the numerical simulation. The demonstrated imaging system, with the advantages of high imaging quality and strong anti-noise property, opens up possibilities for new applications in the THz region.

Sub-Rayleigh imaging via undersampling scanning based on sparsity constraints

We demonstrate that, by undersampling scanning object with a reconstruction algorithm related to compressed sensing, an image with the resolution exceeding the finest resolution defined by the numerical aperture of the system can be obtained. Experimental results show that the measurements needed to achieve sub-Rayleigh resolution enhancement can be less than 10% of the pixels of the object. This method offers a general approach applicable to point-by-point illumination super-resolution techniques.

Quasi noise-free digital holography

One of the main drawbacks of Digital Holography(DH)is the coherent nature of the light source,which severely corrupts the quality of holographic reconstructions.Although numerous techniques to reduce noise in DH have provided good results,holographic noise suppression remains a challenging task.We propose a novel framework that combines the concepts of encoding multiple uncorrelated digital holograms,block grouping and collaborative filtering to achieve quasi noise-free DH reconstructions.The optimized joint action of these different image-denoising methods permits the removal of up to 98%of the noise while preserving the image contrast.The resulting quality of the hologram reconstructions is comparable to the quality achievable with non-coherent techniques and far beyond the current state of art in DH.Experimental validation is provided for both singlewavelength and multi-wavelength DH,and a comparison with the most used holographic denoising methods is performed.

End-to-end deep learning framework for digital holographic reconstruction

Digital holography records the entire wavefront of an object,including amplitude and phase.To reconstruct the object numerically,we can backpropagate the hologram with Fresnel–Kirchhoff integralbased algorithms such as the angular spectrum method and the convolution method.Although effective,these techniques require prior knowledge,such as the object distance,the incident angle between the two beams,and the source wavelength.Undesirable zero-order and twin images have to be removed by an additional filtering operation,which is usually manual and consumes more time in off-axis configuration.In addition,for phase imaging,the phase aberration has to be compensated,and subsequently an unwrapping step is needed to recover the true object thickness.The former either requires additional hardware or strong assumptions,whereas the phase unwrapping algorithms are often sensitive to noise and distortion.Furthermore,for a multisectional object,an all-in-focus image and depth map are desired for many applications,but current approaches tend to be computationally demanding.We propose an end-to-end deep learning framework,called a holographic reconstruction network,to tackle these holographic reconstruction problems.Through this data-driven approach,we show that it is possible to reconstruct a noise-free image that does not require any prior knowledge and can handle phase imaging as well as depth map generation.