Snapshot spectrum depth joint imaging method and system based on deep learning

A technology of deep learning and imaging methods, applied in the field of image processing, can solve the problem of not being able to collect high-resolution (1080p) spectral images and depth images, and achieve the effect of compact size and simple calibration

Active Publication Date: 2020-03-13
UNIV OF SCI & TECH OF CHINA
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Problems solved by technology

[0005] For the requirements of high spatial resolution application scenarios, existing solutions cannot meet the requirements of collecting high-resolution (1080p) spectral images and depth images in dynamic scenarios Require

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  • Snapshot spectrum depth joint imaging method and system based on deep learning
  • Snapshot spectrum depth joint imaging method and system based on deep learning
  • Snapshot spectrum depth joint imaging method and system based on deep learning

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Embodiment Construction

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0025] The embodiment of the present invention provides a snapshot spectrum-depth joint imaging method based on deep learning, which involves the collection and reconstruction of high-resolution (1080p) spectrum and depth image data, and realizes the simultaneous acquisition of spectrum and depth information of dynamic scenes. Under the premise of temporal resolution, the deep learning algorithm is used to reconstruct the high-resolution (1080p) spe...

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Abstract

The invention discloses a snapshot spectrum depth joint imaging method and system based on deep learning. Based on the complementarity between a low-spatial-resolution spectral image and a high-spatial-resolution RGB image shot from different visual angles, a high-spatial-resolution spectral image and a high-spatial-resolution depth image of a scene are reconstructed by using a deep learning algorithm under the condition of not sacrificing the time resolution. In addition, a spectral image and a depth image are obtained, namely reflection characteristics and geometric characteristics of a target scene are obtained. The basic description of the scene can be established according to the characteristics, and then operations such as three-dimensional reconstruction and light rendering can be performed on the target scene. In addition, the imaging system is compact in size and easy to calibrate, and a feasible solution is provided for application of future spectral depth imaging to small equipment such as a mobile phone or an unmanned aerial vehicle.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method and system for joint imaging of snapshot spectrum and depth based on deep learning. Background technique [0002] Spectral information reflects the properties of the spectral dimension of objects and scenes, while depth information reflects the geometric characteristics of objects. It has always been the direction of human efforts to simultaneously obtain more dimensional image information including spectrum and depth. Due to the complex imaging principle of spectral images, the acquisition of spectral images is often at the expense of image spatial resolution or shooting time, and it is more difficult to reconstruct the three-dimensional information of objects on spectral images without sacrificing spatial resolution. [0003] In recent years, due to the advancement of optical instrument technology and the growth of computing power, the fields of spectr...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T5/50G06T7/593G06T7/90G06T17/00
CPCG06T17/00G06T7/596G06T7/90G06T3/4053G06T5/50G06T2207/10036G06T2207/20221
Inventor 熊志伟姚明德张越一
Owner UNIV OF SCI & TECH OF CHINA
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