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1por Goreke, Utku, Gonzales, Ayesha, Shipley, Brandon, Man, Yuncheng, Wulftange, William, An, Ran, Hinczewski, Michael, Gurkan, Umut A.“…We propose to overcome this challenge by a new in vitro imaging method which we call motion blur microscopy (MBM). By decreasing the source light intensity and increasing the integration time during imaging, flowing cells are blurred, allowing us to identify adhered cells. …”
Publicado 2023
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2“…Blind image restoration algorithms for motion blur have been deeply researched in the past years. …”
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3“…Synthetically creating motion blur in two-dimensional (2D) images is a well-understood process and has been used in image processing for developing deblurring systems. …”
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4“…The accuracy of edge detection is significantly reduced when applied to motion-blurred images. In this paper, we propose an effective deblurring method adapted to the edge detection task, utilizing inertial sensors to aid in the deblurring process. …”
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6“…When filming a fast-moving subject using a regular camera rather than a super-high-speed camera, there is often severe motion blur, making it difficult to recognize the exact location and speed of the object in the video. …”
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7“…High-quality medical ultrasound imaging is definitely concerning motion blur, while medical image analysis requires motionless and accurate data acquired by sonographers. …”
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8“…Motion blur is a common artifact in image processing, specifically in e-health services, which is caused by the motion of a camera or scene. …”
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9“…For the 3D reconstruction scene of motion-blurred CT image, this paper consists of two parts: firstly, a GAN image translation network deblurring algorithm is proposed to remove blurred results. …”
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10por Zhou, Wei, Hao, Xingxing, Wang, Kaidi, Zhang, Zhenyang, Yu, Yongxiang, Su, Haonan, Li, Kang, Cao, Xin, Kuijper, Arjan“…Finally, we evaluate the accuracy, robustness and time efficiency of our proposed method with the existing algorithms on the public benchmarks and the natural real motion blurred images. The experimental results demonstrate that the proposed PSF estimation scheme not only could obtain a higher accuracy for the blur angle and blur length, but also demonstrate stronger robustness and higher time efficiency under different circumstances.…”
Publicado 2020
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11“…However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. …”
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12por Inoue, Michiaki, Gu, Qingyi, Jiang, Mingjun, Takaki, Takeshi, Ishii, Idaku, Tajima, Kenji“…This study proposes a novel concept of actuator-driven frame-by-frame intermittent tracking for motion-blur-free video shooting of fast-moving objects. …”
Publicado 2017
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13por Isenkul, M. Erdem“…In a developed test, horizontal and vertical motion blur orientation was applied to natural image samples, and then neural outputs were produced by representing three (original-horizontal-vertical) image groups with the Layer 4 (L4) cortex model. …”
Publicado 2019
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14“…Motion blur is common in video tracking and detection, and severe motion blur can lead to failure in tracking and detection. …”
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15“…Under dynamic conditions, motion blur is introduced to star images obtained by a star sensor. …”
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16“…However, there has been no research on restoration methods of motion blurred finger-vein images that can occur in actual environments. …”
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17“…Various types of motion blur are frequently observed in the images captured by sensors based on thermal and photon detectors. …”
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18“…Video reconstruction from a single motion-blurred image is a challenging problem, which can enhance the capabilities of existing cameras. …”
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19“…In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. …”
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20“…Inspired by the recent success of deep learning models in medical image analysis, we investigate the efficacy of employing generative adversarial networks (GANs) to address motion blurs in brain MRI scans. We cast the problem as a blind deconvolution task where a neural network is trained to guess a blurring kernel that produced the observed corruption. …”
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