Deep convolutional neural networks (CNN) have been applied for image dehazing tasks, where the residual network (ResNet) is often adopted as the basic component to avoid the vanishing gradient problem. Recently, many works indicate that the ResNet can be considered as the explicit Euler forward approximation of an ordinary differential equation (ODE). In this paper, we extend the explicit forward approximation to the implicit backward counterpart, which can be realized via a recursive neural network, named IM-block. Given that, we propose an efficient end-to-end multi-level implicit network (MI-Net) for the single image dehazing problem. Moreover, multi-level fusing (MLF) mechanism and residual channel attention block (RCA-block) are adopted to boost performance of our network. Experiments on several dehazing benchmark datasets demonstrate that our method outperforms existing methods and achieves the state-of-the-art performance.

Jiawei Shen Zhuoyan Li Lei Yu Gui-Song Xia Wen Yang

The Fourier-Transform ghost imaging of both amplitude-only and pure-phase objects was experimentally observed with classical incoherent light at Fresnel distance by a new lensless scheme. The experimental results are in good agreement with the standard Fourier-transform of the corresponding objects. This scheme provides a new route towards aberration-free diffraction-limited 3D images with classically incoherent thermal light, which have no resolution and depth-of-field limitations of lens-based tomographic systems.

Minghui Zhang Qing Wei Xia Shen Yongfeng Liu Honglin Liu Jing Cheng Shensheng Han

We report, for the first time, the observation of sub-wavelength coherent image of a pure phase object with thermal light,which represents an accurate Fourier transform. We demonstrate that ghost-imaging scheme (GI) retrieves amplitude transmittance knowledge of objects rather than the transmitted intensities as the HBT-type imaging scheme does.

Minghui Zhang Qing Wei Xia Shen Yongfeng Liu Honglin Liu Yanfeng Bai Shensheng Han

As one of important analysis tools, microscopes with high spatial resolution are indispensable for scientific research and medical diagnosis, and much attention is always focused on the improvement of resolution. Over the past decade, a novel technique called ghost imaging has been developed that may provide a new approach toward increasing the resolution of an imaging system. In this paper, we introduce this technique into microscopes for the first time and report a proof-of-principle experimental demonstration of a microscope scheme based on ghost imaging.

Pengli Zhang Wenlin Gong Xia Shen Dajie Huang Shensheng Han

Ghost imaging with thermal light in scattering media is investigated. We demonstrated both theoretically and experimentally for the first time that the image with high quality can still be obtained in the scattering media by ghost imaging. The scattering effect on the qualities of the images obtained when the object is illuminated directly by the thermal light and ghost imaging is analyzed theoretically. Its potential applications are also discussed.

Wenlin Gong Pengli Zhang Xia Shen Shensheng Han

Imaging with the second-order correlation of two light fields is a method to image an object by two-photon interference involving a joint detection of two photons at distant space-time points. We demonstrate for the first time that an image with high quality can still be obtained in the scattering media by applying the second-order correlation of illuminating light field. The scattering effect on the visibility of images is analyzed both theoretically and experimentally. Potential applications and the methods to further improve the visibility of the images in scattering media are also discussed.

Wenlin Gong Pengli Zhang Xia Shen Shensheng Han

Correlated imaging through atmospheric turbulence is studied, and the analytical expressions describing turbulence effects on image resolution are derived. Compared with direct imaging, correlated imaging can reduce the influence of turbulence to a certain extent and reconstruct high-resolution images. The result is backed up by numerical simulations, in which turbulence-induced phase perturbations are simulated by random phase screens inserting propagation paths.

Pengli Zhang Wenlin Gong Xia Shen Shensheng Han

In this article, we investigate additive properties of the Drazin inverse of elements in rings and algebras over an arbitrary field. Under the weakly commutative condition of $ab = \lambda ba$, we show that $a-b$ is Drazin invertible if and only if $aa^{D}(a-b)bb^{D}$ is Drazin invertible. Next, we give explicit representations of $(a+b)^{D}$, as a function of $a, b, a^{D}$ and $b^{D}$, under the conditions $a^{3}b = ba$ and $b^{3}a = ab$.

Long Wang Huihui Zhu Xia Zhu Jianlong Chen

This paper aims to provide a description of totally isotropic Willmore two-spheres and their adjoint transforms. We first recall the isotropic harmonic maps which are introduced by H\'elein, Xia-Shen and Ma for the study of Willmore surfaces. Then we derive a description of the normalized potential (some Lie algebra valued meromorphic 1-forms) of totally isotropic Willmore two-spheres in terms of the isotropic harmonic maps. In particular, the corresponding isotropic harmonic maps are of finite uniton type. The proof also contains a concrete way to construct examples of totally isotropic Willmore two-spheres and their adjoint transforms. As illustrations, two kinds of examples are obtained this way.

Peng Wang

Adverse drug reactions (ADRs) induced from high-order drug-drug interactions (DDIs) due to polypharmacy represent a significant public health problem. In this paper, we formally formulate the to-avoid and safe (with respect to ADRs) drug recommendation problems when multiple drugs have been taken simultaneously. We develop a joint model with a recommendation component and an ADR label prediction component to recommend for a prescription a set of to-avoid drugs that will induce ADRs if taken together with the prescription. We also develop real drug-drug interaction datasets and corresponding evaluation protocols. Our experimental results on real datasets demonstrate the strong performance of the joint model compared to other baseline methods.

Wen-Hao Chiang Li Shen Lang Li Xia Ning