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Among the approaches in three-dimensional (3D) single molecule localization microscopy, there are several point spread function (PSF) engineering approaches, in which depth information of molecules is encoded in 2D images. Usually, the molecules are excited sparsely in each raw image. The consequence is that the temporal resolution has to be sacrificed. In order to improve temporal resolution and ensure localization accuracy, we propose a method, SH-CS, based on light needle excitation, detection system with single helix-point spread function (SH-PSF), and compressed sensing (CS). Although the SH-CS method still has a limitation about the molecule density, it is suited for relatively dense molecules. For each light needle scanning position, an SH image of excited molecules is processed with CS algorithm to decode their axial information. Simulations demonstrated, for random distributed 1–15 molecules in depth range of 4 μm, the axial localization accuracy is 12.1–73.5 nm. The feasibility of this method is validated with a designed 3D sample composed of fluorescent beads.

Metasurfaces are two-dimensional arrangements of antennas that control the propagation of electromagnetic waves with a subwavelength thickness and resolution. Previously, metasurfaces have been mostly used to obtain the function of a single optical element. Here, we demonstrate a plasmonic metasurface that represents the combination of a phase mask generating a double-helix point spread function (DH-PSF) and a metalens for imaging. DH-PSF has been widely studied in three-dimensional (3D) super-resolution imaging, biomedical imaging, and particle tracking, but the current DH-PSFs are inefficient, bulky, and difficult to integrate. The multielement metasurface, which we label as DH-metalens, enables a DH-PSF with transfer efficiency up to 70.3% and an ultrahigh level of optical system integration, three orders of magnitude smaller than those realized by conventional phase elements. Moreover, the demonstrated DH-metalens can work in broadband visible wavelengths and in multiple incident polarization states. Finally, we demonstrate the application of the DH-metalens in 3D imaging of point sources. These results pave ways for realizing integrated DH-PSFs, which have applications in 3D super-resolution microscopy, single particle tracking/imaging, and machine vision.

In recent years, there have been multiple advances in positron emission tomography/computed tomography (PET/CT) that improve cancer imaging. The present generation of PET/CT scanners introduces new hardware, software, and acquisition methods. This review describes these new developments, which include time-of-flight (TOF), point-spread-function (PSF), maximum-a-posteriori (MAP) based reconstruction, smaller voxels, respiratory gating, metal artefact reduction, and administration of quadratic weight-dependent 18 F–fluorodeoxyglucose (FDG) activity. Also, hardware developments such as continuous bed motion (CBM), (digital) solid-state photodetectors and combined PET and magnetic resonance (MR) systems are explained. These novel techniques have a significant impact on cancer imaging, as they result in better image quality, improved small lesion detectability, and more accurate quantification of radiopharmaceutical uptake. This influences cancer diagnosis and staging, as well as therapy response monitoring and radiotherapy planning. Finally, the possible impact of these developments on the European Association of Nuclear Medicine (EANM) guidelines and EANM Research Ltd. (EARL) accreditation for FDG-PET/CT tumor imaging is discussed.

When using a monocular camera for detection or observation, one only obtain two-dimensional information, which is far from adequate for surgical robot manipulation and workpiece detection. Therefore, at this scale, obtaining three-dimensional information of the observed object, especially the depth information estimation of the surface points of each object, has become a key issue. This paper proposes two methods to solve the problem of depth estimation of defiant images in microscopic scenes. These are the depth estimation method of the defocused image based on a Markov random field, and the method based on geometric constraints. According to the real aperture imaging principle, the geometric constraints on the relative defocus parameters of the point spread function are derived, which improves the traditional iterative method and improves the algorithm’s efficiency.

Ultrathin metasurfaces have shown the capability to influence all aspects of light propagation. This has made them promising options for replacing conventional bulky imaging optics while adding advantageous optical properties or functionalities. We demonstrate that such metasurfaces can also be applied for single-lens three-dimensional (3-D) imaging based on a specifically engineered point-spread function (PSF). Using Huygens’ metasurfaces with high transmission, we design and realize a phase mask that implements a rotating PSF for 3-D imaging. We experimentally characterize the properties of the realized double-helix PSF, finding that it can uniquely encode object distances within a wide range. Furthermore, we experimentally demonstrate wide-field depth retrieval within a 3-D scene, showing the suitability of metasurfaces to realize optics for 3-D imaging, using just a single camera and lens system.

Mathematical properties of the ensquared energy functions for apodized point-spread function (PSF) are presented. An expression of ensquared energy for the apodized point Spread function of the optical system with a circular aperture was derived using a parabolic apodized filter with a different arrangement N =1, 2,3,4. The results obtained were discussed graphically.

In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future labor shortage and shortage of engineers. In this paper, a method to estimate parameters of motion blur for Point Spread Function (PSF) is mainly discussed, where we assume that there are two main degradation factors caused by the camera, out-of-focus blur and motion blur. A major contribution of this paper is that the parameters can properly be estimated from a sub-image of the object under inspection if the sub-image contains uniform speckled texture. Here, the cepstrum of the sub-image is fully utilized. Then, a filter convoluted PSF which consists of convolution with PSF (motion blur) and PSF (out-of focus blur) can be utilized for deconvolution of the blurred image for sharpening with significant effect. PSF (out-of-focus blur) is a constant function unique to each camera and lens, and can be confirmed before or after shooting. PSF (motion blur), on the other hand, needs to be estimated on a case-by-case basis since the amount and direction of camera movement varies depending on the time of shooting. Previous research papers have sometimes encountered difficulties in estimating the parameters of motion blur because of the emphasis on generality. In this paper, the main object is made of concrete, and on the surface of it there are speckled textures. We hypothesized that we can narrow down the candidates of parameters of motion blur by using these speckled patterns. To verify this hypothesis, we conducted experiments to confirm and examine the following two points using a general-purpose camera used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. 2. Selection method of multiple images to narrow down the candidate minima of the cepstrum. It is novel that the parameters of motion blur can be well estimated by using the unique speckled pattern on the surface of the object.

In synchrotron radiation X‐ray imaging, the imaging field of view and spatial resolution are mutually restricted, which makes it impossible to have both a large field of view and high resolution when carrying out experiments. Constructing an oversampled image through the micro‐scanning method and using the deconvolution algorithm to eliminate the point spread function introduced by pixel overlap can increase the resolution under a fixed imaging field of view, thereby improving the ratio of the field of view to the spatial resolution. In this paper, numerical simulation and synchrotron radiation experiments are carried out with a different number of micro‐scanning steps. In numerical simulation experiments only affected by the image pixel size, as the number of micro‐scanning steps increases, the ability of the oversampled image with deconvolution to improve the resolution is stronger. The achievable resolution of the oversampled image with deconvolution is basically the same as that of the sample image. In the synchrotron radiation experiments, the resolution of the oversampled image with deconvolution in the 2 × 2 mode is significantly improved. However, as the number of micro‐scanning steps increases, the resolution improvement is limited, or even no longer improved. Finally, by analyzing the results of numerical simulation and synchrotron radiation experiments, three factors (four other factors affecting the resolution besides the camera resolution, translational accuracy of micro‐scanning, and the signal‐to‐noise ratio of projections) affecting the micro‐scanning method are proposed and verified by experiments. In synchrotron radiation X‐ray imaging, the spatial resolution under a fixed field of view is improved using the micro‐scanning method.

To solve the problem on inaccuracy when estimating the point spread function (PSF) of the ideal original image in traditional projection onto convex set (POCS) super-resolution (SR) reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR) remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the highresolution (HR) image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40) three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method.

An experimental procedure for transmission X-ray ghost imaging using synchrotron light is presented. Hard X-rays from an undulator were divided by a beamsplitter to produce two copies of a speckled incident beam. Both beams were simultaneously measured on an indirect pixellated detector and the intensity correlation between the two copies was used to retrieve the ghost image of samples placed in one of the two beams, without measuring the samples directly. Aiming at future practical uses of X-ray ghost imaging, the authors discuss details regarding data acquisition, image reconstruction strategies and measure the point-spread function of the ghost-imaging system. This approach may become relevant for applications of ghost imaging with X-ray sources such as undulators in storage rings, free-electron lasers and lower-coherence laboratory facilities.