Zhoudoherty4389

Tree trunk diameter and tree species are two of the most important parameters in analyzing trees in urban areas and forests. Conventionally, diameters have been measured manually, and the species were determined by sight. An automated tool for these assessments was developed. Tree trunks are automatically detected from captured stereo images. Then, tree trunk diameters are estimated, and the species are determined. The developed graphical user interface tool enables fast and accurate estimation even while one is walking, which reduces the time spent in measuring trees.The defect properties of CH3NH3PbI3 solar cells with efficiencies ranging from 7.70% to 12.51% were investigated using admittance spectroscopy measurements. Trap levels of the same kind with activation energies varied in the range of 0.16-0.23 eV above the valence band were found for different samples and identified as an interface-type defect. Moreover, the defect parameters, including the capture cross section of the holes, capture lifetime of the holes, and defect density, were extracted, and their relationships with the cell efficiencies were investigated. The results indicated that, compared with other parameters, defect density is a critical factor for CH3NH3PbI3 solar cell performance.In this study, a method to automatically segment plant leaves from three-dimensional (3D) images using structure from motion is proposed. First, leaves in the 3D images are roughly segmented using a region-growing method in which near points with distances less than 0.2 cm are assigned to the same group. Bucladesine datasheet By repeating this process, the leaves not touching each other can be segmented. Then, each segmented leaf is projected onto two-dimensional (2D) images, and the watershed algorithm is executed. This process successfully segments overlapping leaves.Fiber bundles have become widely adopted for use in endoscopy, live-organism imaging, and other imaging applications. An inherent consequence of imaging with these bundles is the introduction of a honeycomb-like artifact that arises from the inter-fiber spacing, which obscures features of objects in the image. This artifact subsequently limits applicability and can make interpretation of the image-based data difficult. This work presents a method to reduce this artifact by on-axis rotation of the fiber bundle. Fiber bundle images were first low-pass and median filtered to improve image quality. Consecutive filtered images with rotated samples were then co-registered and averaged to generate a final, reconstructed image. The results demonstrate removal of the artifacts, in addition to increased signal contrast and signal-to-noise ratio. This approach combines digital filtering and spatial resampling to reconstruct higher-quality images, enhancing the utility of images acquired using fiber bundles.A fiber-optic Fabry-Perot (FP) interferometer integrated with an adaptive fiber-ring laser is configured as a switchable multi-wavelength fiber laser that can be utilized for ultrasound detection. Because the FP sensor acts as a wavelength filter and a reflector of the fiber-ring laser, the reflective spectrum of the FP sensor changes due to static/dynamic strains, and the wavelength of the laser output shifts accordingly, which is subsequently converted into a corresponding phase shift and demodulated by an unbalanced interferometer. By carefully controlling the polarization of the system, the lasing outputs with a side-mode suppression ratio higher than 30 dB can be obtained, and the lasing linewidth is much narrower than that of the spectrum of the FP sensor. The experiments show that the proposed sensing system has high sensitivity for ultrasound detection and can be adaptive to the low-frequency drifts due to environmental noise.In a multirotation computation imaging system, the fidelity of the reconstructed result is limited by the accuracy of the estimated rotation angles. Here, an accurate angle detection method using image moment is proposed to estimate angles of diffraction images. The second moment of a digital image is adopted as the rotational inertia in order to estimate angles of diffraction images. Compared with previous versions based on Radon/Hough transform, it has higher accuracy and is simultaneously time-saving, which is verified in both simulation and experiment. The angle error of moment method is narrowed down within 0.1°, or even less, and it also can perform well in sample diversity or when slightly out of focus.Diffractive lenses, such as Fresnel zone plates, photon sieves, and their modified versions, have been of significant recent interest in high-resolution imaging applications. As the advent of diffractive lens systems with different configurations expands, the fast and accurate simulation of these systems becomes crucial for both the design and image reconstruction tasks. Here we present a fast and accurate method for computing the 2D point-spread function (PSF) of an arbitrary diffractive lens. The method is based on the recently derived closed-form mathematical formula for the PSF and the transfer function of a diffractive lens. In the method, first, the samples of the transfer function are computed using the transmittance function of the diffractive lens, and then the inverse Fourier transform of this transfer function is computed to obtain the PSF. For accurate computation, the selection of the sampling parameters is handled with care, and simple selection rules are provided for this purpose. The developed method requires a single fast Fourier transform, and, therefore, has little computational complexity. Moreover, it is also applicable to any diffractive lens configuration with arbitrary-shaped structures and modulation. As a result, this fast and accurate PSF computation method enables efficient simulation, analysis, and development of diffractive lens systems under both focused and defocused settings.Random phase masks serve as secret keys and play a vital role in double random phase encoding architecture. In this paper, we propose a new, to the best of our knowledge, method to generate the random phase masks using the chaotic Henon map and fingerprint. We then extend the generated chaotic fingerprint phase masks to the Fourier transform domain, fractional Fourier transform domain, Fresnel transform domain, and Gyrator transform domain to encrypt color images. In these four color image encryption schemes, the fingerprint and chaotic parameters serve as secret keys directly, and the chaotic fingerprint phase masks are just used as interim variables and functions. If the sender and receiver share the fingerprint, only the chaotic parameters are needed to transmit over the network. Thus, the management and transmission of the secret keys in these four encryption schemes are convenient. In addition, the fingerprint keys which are strongly linked with the sender or receiver can enhance the security of these four encryption schemes greatly.