A light field (LF), which is represented as a set of dense multi view images, has been utilized in various 3D applications. To make LF acquisition more efficient, researchers have investi gated compressive sensing methods by incorporating modula tion or coding functions into the camera. In this work, we in vestigate a challenging case of compressive LF acquisition in which an entire LF should be reconstructed from only a single coded image. To achieve this goal, we propose a new mod ulation scheme called factorized modulation that can approx imate arbitrary 4D modulation patterns in a factorized man ner. Our method can be hardwareimplemented by combining the architectures for coded aperture and pixelwise coded ex posure imaging. The modulation pattern is jointly optimized with a CNNbased reconstruction algorithm. Our method is validated through extensive evaluations against other modu lation schemes.
A light field (LF), which is represented as a set of dense, multi-view images, has been used in various 3D applications. To make LF acquisition more efficient, researchers have investigated compressive sensing methods by incorporating certain coding functionalities into a camera. In this paper, we focus on a challenging case called snapshot compressive LF imaging, in which an entire LF is reconstructed from only a single acquired image. To embed a large amount of LF information in a single image, we consider two promising methods based on rapid optical control during a single exposure: time-multiplexed coded aperture (TMCA) and coded focal stack (CFS), which were proposed individually in previous works. Both TMCA and CFS can be interpreted in a unified manner as extensions of the coded aperture (CA) and focal stack (FS) methods, respectively. By developing a unified algorithm pipeline for TMCA and CFS, based on deep neural networks, we evaluated their performance with respect to other possible imaging methods. We found that both TMCA and CFS can achieve better reconstruction quality than the other snapshot methods, and they also perform reasonably well compared to methods using multiple acquired images. To our knowledge, we are the first to present an overall discussion of TMCA and CFS and to compare and validate their effectiveness in the context of compressive LF imaging.
Guided wave inspection is expected especially for buried piping because it can be applied easily to such piping requiring only its partial digging from the ground. However, in buried piping, the attenuation coefficient is extremely large compared with that in above-ground piping because the leaky mode guided wave (LTGW) propagates in buried piping and its energy leaks into the adjacent surrounding material as a bulk shear wave. Petrolatum anticorrosion grease (PAG) is the most widely used as the coating material on the pipe surface before burying piping in sand or soil, which is a viscous material with a temperature-dependent shear wave velocity. In this paper, attenuation characteristics of the LTGW are shown theoretically and experimentally. The theoretical calculations explain very well the experimental results measured. The temperature dependence of the attenuation coefficient is discussed with the theoretical outcomes.
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