Latest Progress in Computational Imaging Technology and Application

Xiaopeng, 邵晓鹏 Shao; Fei, 刘飞 Liu; Wei, 李伟 Li; Liming, 杨力铭 Yang; Siyuan, 杨思原 Yang; Jiawei, 刘佳维 Liu

doi:10.3788/lop57.020001

Cited by 18 publications

(6 citation statements)

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“…The 31 components detected the target using the edge aperture and accurately identified the target using the center aperture with a full field of view of 53.9 • . In Shao et al (2020) research group designed a multi-aperture system with a full field of view of 123.5 • × 38.5 • . The system also supported real-time viewing and other functions, such as images, videos, and other information.…”

Section: Single-scale and Multi-aperture Imaging Technologymentioning

confidence: 99%

Computational optical imaging: challenges, opportunities, new trends, and emerging applications

Xiang,

Liu,

Liu

et al. 2024

Front. Imaging.

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Computational imaging technology (CIT), with its many variations, addresses the limitations of industrial design. CIT can effectively overcome the bottlenecks in physical information acquisition, model development, and resolution by being tightly coupled with mathematical calculations and signal processing in information acquisition, transmission, and interpretation. Qualitative improvements are achieved in the dimensions, scale, and resolution of the information. Therefore, in this review, the concepts and meaning of CIT are summarized before establishing a real CIT system. The basic common problems and relevant challenging technologies are analyzed, particularly the non-linear imaging model. The five typical imaging requirements–distance, resolution, applicability, field of view, and system size–are detailed. The corresponding key issues of super-large-aperture imaging systems, imaging beyond the diffraction limit, bionic optics, interpretation of light field information, computational optical system design, and computational detectors are also discussed. This review provides a global perspective for researchers to promote technological developments and applications.

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Section: Single-scale and Multi-aperture Imaging Technologymentioning

confidence: 99%

Computational optical imaging: challenges, opportunities, new trends, and emerging applications

Xiang,

Liu,

Liu

et al. 2024

Front. Imaging.

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“…As an important approach for humans to record and perceive environmental information, traditional optoelectronic imaging techniques are increasingly ineffective due to the loss of high-dimensional information [1,2]. With advancements in new sensors, data transmission, and storage, more information about the light field such as phase, polarization, and spectral information can be efficiently detected and recorded [3][4][5][6], which helps to construct a functional relationship between the reflected light information and the contour of the object surface to obtain 3D information.…”

Section: Introductionmentioning

confidence: 99%

Polarization 3D imaging technology: a review

Liu

Cai

et al. 2023

Front. Phys.

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Polarization three-dimensional (3D) imaging technology has received extensive attention in recent years because of its advantages of high accuracy, long detection distance, simplicity, and low cost. The ambiguity in the normal obtained by the polarization characteristics of the target’s specular or diffuse reflected light limits the development of polarization 3D imaging technology. Over the past few decades, many shape from polarization techniques have been proposed to address the ambiguity issues, i.e., high-precision normal acquisition. Meanwhile, some polarization 3D imaging techniques attempt to extend experimental objects to complex specific targets and scenarios through a learning-based approach. Additionally, other problems and related solutions in polarization 3D imaging technology are also investigated. In this paper, the fundamental principles behind these technologies will be elucidated, experimental results will be presented to demonstrate the capabilities and limitations of these popular technologies, and finally, our perspectives on the remaining challenges of the polarization 3D imaging technology will be presented.

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“…Its geography, climatic conditions, tourism resources, marine living resources and energy resources are very rich [1]. Underwater optical imaging technology is an important technology in marine research, marine resources exploration, topographic and topographic mapping, Underwater Archaeology and marine biology research [1] [2] [3] [4]. In 2000, J. G. Walker et al [5] proposed polarization subtraction technology to detect underwater objects.…”

Section: Introductionmentioning

confidence: 99%

Underwater polarization defogging technology based on Stokes

Wang

Zhou

Wang

et al. 2023

International Conference on Precision Instruments and Optical Engineering (PIOE 2022)

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This paper mainly discusses the underwater fog technology, and mainly uses some image evaluation algorithms. Compared with other image processing algorithms, it improves the running speed of the algorithm. In short, the underwater image denoising and contrast after processing are better than the traditional image polarization defogging algorithm. The experiment specifically uses the split focus plane polarization imaging system to collect polarization pictures from multiple angles in multiple underwater scenes, and calculate its polarization stokes vector, calculate the polarization information of the scene through the stokes vector, use the general light source and linear polarization light source to illuminate the diffuse reflection and specular reflection targets respectively, compare the polarization information of different scenes, and get that the polarization information distribution of the background and target of the scene using polarization light source is clearer than that of the general light source. Then, a stokes polarization defogging algorithm is proposed. The polarization degree information calculated by stokes vector is compared with the transmission information obtained by the dark channel prior algorithm. It is found that under the condition of using polarized light source and uniform illumination, the transmission of scene can be predicted by DOP (Degree of polarization) calculated by stokes vector and used for image defogging, then some image evaluation algorithms are used to compare it with other image processing algorithms, which improves the running speed of the algorithm. The denoising and contrast of the underwater image after processing are better than the traditional image polarization defogging algorithm.

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Latest Progress in Computational Imaging Technology and Application

Cited by 18 publications

References 0 publications

Computational optical imaging: challenges, opportunities, new trends, and emerging applications

Computational optical imaging: challenges, opportunities, new trends, and emerging applications

Polarization 3D imaging technology: a review

Underwater polarization defogging technology based on Stokes

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