作者：
Wang, LihuiCui, JianjiangTabata, SatoshiIshikawa, MasatoshiUniv Tokyo
Grad Sch Informat Sci & Technol Dept Creat Informat Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan Northeastern Univ
Coll Informat Sci & Engn Inst Intelligent Syst 11 Lane 3Wenhua Rd Shenyang 110819 Liaoning Peoples R China Univ Tokyo
Grad Sch Informat Sci & Technol Dept Informat Phys & Comp Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan
A large open aperture in an optical system can capture high-resolution images but yields a shallow depth of field. To overcome this issue, we investigated a low-cost, readily available method for retrofitting microsco...
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A large open aperture in an optical system can capture high-resolution images but yields a shallow depth of field. To overcome this issue, we investigated a low-cost, readily available method for retrofitting microscopy imaging systems to achieve 3D focus scanning in this study. Specifically, a procedure for fabricating variable focus spinners with dissimilar plates was introduced, and a sequence of 12 images was captured in different focal planes. The image scale and phase were corrected, and the in-focus pixels were abstracted by employing the Laplacian operator. Finally, an all-in-focus sharp image was generated, and a depth map was obtained. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
It is challenging to calibrate multiple camera-projector pairs for multi-view 3D surface reconstruction based on structured light. Here, we present a new automated calibration method for high-speed multi-camera-projec...
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It is challenging to calibrate multiple camera-projector pairs for multi-view 3D surface reconstruction based on structured light. Here, we present a new automated calibration method for high-speed multi-camera-projector systems. The method uses printed and projected dot patterns on a planar calibration target, which is moved by hand in the calibration volume. Calibration is enabled by automated imageprocessing and bundle-adjusted parameter optimization. We determined the performance of our method by 3D reconstructing a sphere. The accuracy is -0.03 +/- 0.09 % as a percentage of the diameter of the calibration volume. Applications include quality control, autonomous systems, engineering measurements, and motion capture, such as the preliminary 3D reconstruction of a bird in flight we present here. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
In inter-satellite laser communication systems, accurate positioning of the beacon is essential for establishing a steady laser communication link. For inter-satellite optical communication, the main factor affecting ...
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In inter-satellite laser communication systems, accurate positioning of the beacon is essential for establishing a steady laser communication link. For inter-satellite optical communication, the main factor affecting the acquisition and tracking of the beacon is the background noise, such as stellar background light. In this study, we considered the effect of the background noise on a beacon in inter-satellite optical communication and proposed a new recognition algorithm for the beacon, which uses the optical flow vector obtained from the image data. We verified the feasibility of this method by performing simulation analysis and experiments. Both simulation and experiments showed that the new algorithm could accurately obtain the position of the centroid of the beacon under the effect of the background light. Furthermore, considering the identification probability of a light spot through the background light, the locating accuracy of the new algorithm was higher than that of the conventional gray centroid algorithm. Therefore, this new approach would be beneficial for the design of satellite-to-ground optical communication systems. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and the performance of automatic analysis. Edge preservation is an important issue for speckle reduction. In this paper, we propose a...
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Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and the performance of automatic analysis. Edge preservation is an important issue for speckle reduction. In this paper, we propose an end-to-end framework for simultaneous speckle reduction and contrast enhancement for retinal OCT images based on the conditional generative adversarial network (cGAN). The edge loss function is added to the final objective so that the model is sensitive to the edge-related details. We also propose a novel method for obtaining clean images for training from outputs of commercial OCT scanners. The results show that the overall denoising performance of the proposed method is better than other traditional methods and deep learning methods. The proposed model also has good generalization ability and is capable of despeckling different types of retinal OCT images. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
In digital holography, the inherited speckle noise degrades imaging quality due to the coherent laser source. To overcome this problem, a hybrid method for speckle noise reduction is presented by combining a novel ang...
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In digital holography, the inherited speckle noise degrades imaging quality due to the coherent laser source. To overcome this problem, a hybrid method for speckle noise reduction is presented by combining a novel angular diversity approach with the block-matching and 3D filtering (BM3D) algorithm. A serial of holograms is first captured by the proposed recording approach, and then the image with high signal-to-noise ratio is obtained by averaging multiple reconstructed intensity images. Finally, the residual noise in the averaged image is further eliminated by the BM3D filtering algorithm. The speckle noise is significantly suppressed, and a nearly speckle-free image can be obtained. Experimental results demonstrate the effectiveness of the proposed method. (c) 2019 Optical Society of America
This paper describes an algorithm for distinguishing between images of two classes of objects: artificial and natural. An approximation to the image is generated using graphical elements similar to the receptor fields...
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This paper describes an algorithm for distinguishing between images of two classes of objects: artificial and natural. An approximation to the image is generated using graphical elements similar to the receptor fields of neurons in the primary visual cortex (Zone VI). We show that the approximation-error distribution for natural-object images lies at higher values of the approximation error than that for artificial-object images. This difference makes it possible to detect artificial objects against natural backgrounds. (C) 2018 Optical Society of America
Background: The epigenomics data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specifi...
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Background: The epigenomics data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional annotation problem, within the bounds of the hardware constraints and the model's complexity. In our system Aikyatan, we annotate distal epigenomic regulatory sites, e.g., enhancers. Specifically, we develop a binary classifier that classifies genome sequences as distal regulatory regions or not, given their histone modifications' combinatorial signatures. This problem is challenging because the regulatory regions are distal to the genes, with diverse signatures across classes (e.g., enhancers and insulators) and even within each class (e.g., different enhancer sub-classes). Results We develop a suite of ML models, under the banner Aikyatan, including SVM models, random forest variants, and deep learning architectures, for distal regulatory element (DRE) detection. We demonstrate, with strong empirical evidence, deep learning approaches have a computational advantage. Plus, convolutional neural networks (CNN) provide the best-in-class accuracy, superior to the vanilla variant. With the human embryonic cell line H1, CNN achieves an accuracy of 97.9% and an order of magnitude lower runtime than the kernel SVM. Running on a GPU, the training time is sped up 21x and 30x (over CPU) for DNN and CNN, respectively. Finally, our CNN model enjoys superior prediction performance vis-'a-vis the competition. Specifically, Aikyatan-CNN achieved 40% higher validation rate versus CSIANN and the same accuracy as RFECS. Conclusions Our exhaustive experiments using an array of ML tools validate the need for a model that is not only expressive but can scale with increasing data volumes and diversity. In addition, a subset of these datasets have image-like properties and benefit from spatial pooling of features. Our Aikyatan suite leverages diverse epigenomic d
Accurate measurements of the oceanic whitecap coverage from whitecap images are required for better understanding the air - gas transfer and aerosol production processes. However, this is a challenging task because th...
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Accurate measurements of the oceanic whitecap coverage from whitecap images are required for better understanding the air - gas transfer and aerosol production processes. However, this is a challenging task because the whitecap patches are formed immediately after the wave breaks and are spread over a wide area. The main challenges in designing a whitecap-imaging instrument are the small field of view of the camera lens, processing large numbers of images, recording data over long time periods, and deployment difficulties in stormy conditions. This paper describes the design of a novel high-resolution optical instrument for imaging oceanic whitecaps and the automated algorithm processing the collected images. The instrument was successfully deployed in 2013 as part of the HiWINGS campaign in the North Atlantic Ocean. The instrument uses a fish-eye camera lens to image the whitecaps in wide angle of view (180 degrees).
We have built a hyperspectral database of 42 fruits and vegetables. Both the outside (skin) and inside of the objects were imaged. We used a Specim VNIR HS-CL-30-V8E-OEM mirror-scanning hyperspectral camera and took p...
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We have built a hyperspectral database of 42 fruits and vegetables. Both the outside (skin) and inside of the objects were imaged. We used a Specim VNIR HS-CL-30-V8E-OEM mirror-scanning hyperspectral camera and took pictures at a spatial resolution of similar to 57 px/deg by 800 pixels at a wavelength resolution of similar to 1.12 nm. A stable, broadband illuminant was used. images and software are freely available on our webserver (http://***/GHIFVD;pronounced "gift"). We performed two kinds of analyses on these images. First, when comparing the insides and outsides of the objects, we observed that the insides were lighter than the skins, and that the hues of the insides and skins were significantly correlated (circular correlation = 0.638). Second, we compared the color distribution within each object to corresponding human color discrimination thresholds. We found a significant correlation (0.75) between the orientation of ellipses fit to the chromaticity distributions of our fruits and vegetables with the orientations of interpolated MacAdam discrimination ellipses. This indicates a close relationship between sensory processing and the characteristics of environmental objects. (c) 2018 Optical Society of America
Measurements of multidispersed bubble diameter are important in hydraulics, biology, and other such fields. Interferometric particle imaging (IPI) systems are used to measure the bubble diameter. In geometric approxim...
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Measurements of multidispersed bubble diameter are important in hydraulics, biology, and other such fields. Interferometric particle imaging (IPI) systems are used to measure the bubble diameter. In geometric approximation, the scattering angle cannot be greater than 2 arccos m. We propose a universal method for calculating the bubble diameter at wide scattering angles and use an IPI system to measure the bubble-size distribution at 90 degrees and 45 degrees. The particle size distributions measured at two angles are consistent with each other. The results of this study indicate that this method is suitable for measuring the bubble-size distribution. (C) 2018 Optical Society of America
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