Depth-layer weighted prediction method for a full-color polygon-based holographic system with real objects

Zhao, Yu; Piao, Yan; Jeon, Seokhee; Kim, Nam

doi:10.1364/ol.42.002599

Cited by 22 publications

(5 citation statements)

References 15 publications

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“…The Vector-Angular Distance (VAD) color difference equation is a method used to quantify the difference between two colors in the RGB color space [26][27][28]. The VAD equation [29] takes into account both the magnitude and the angular information of the color vectors, as defined by…”

Section: Vector-angular Distance (Vad)mentioning

confidence: 99%

Rapeseed Seed Coat Color Classification Based on the Visibility Graph Algorithm and Hyperspectral Technique

Zou,

Zhu,

Wang

et al. 2024

Agronomy

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Information technology and statistical modeling have made significant contributions to smart agriculture. Machine vision and hyperspectral technologies, with their non-destructive and real-time capabilities, have been extensively utilized in the non-destructive diagnosis and quality monitoring of crops and seeds, becoming essential tools in traditional agriculture. This work applies these techniques to address the color classification of rapeseed, which is of great significance in the field of rapeseed growth diagnosis research. To bridge the gap between machine vision and hyperspectral technology, a framework is developed that includes seed color calibration, spectral feature extraction and fusion, and the recognition modeling of three seed colors using four machine learning methods. Three categories of rapeseed coat colors are calibrated based on visual perception and vector-square distance methods. A fast-weighted visibility graph method is employed to map the spectral reflectance sequences to complex networks, and five global network attributes are extracted to fuse the full-band reflectance as model input. The experimental results demonstrate that the classification recognition rate of the fused feature reaches 0.943 under the XGBoost model, confirming the effectiveness of the network features as a complement to the spectral reflectance. The high recognition accuracy and simple operation process of the framework support the further application of hyperspectral technology to analyze the quality of rapeseed.

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Section: Vector-angular Distance (Vad)mentioning

confidence: 99%

Rapeseed Seed Coat Color Classification Based on the Visibility Graph Algorithm and Hyperspectral Technique

Zou,

Zhu,

Wang

et al. 2024

Agronomy

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“…However, it is hard to meet the actual needs of holographic video calls and real-time holographic video displays due to its difficulty in obtaining real-time data and calculating and insufficient reconstruction quality. Therefore, for color holographic display, the applicant and his team have constructed a color holographic display system for natural objects [13], but due to the acquisition speed and reconstruction speed, the color holographic display system is difficult to achieve real-time standards.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a full-color holographic system using RGB-D salient object detection

Yang

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

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Recently, a real objects-based full-color holographic display system usually uses a DSLR camera array or depth camera to collect data, and then relies on a spatial light modulator to modulate the input light source for the reconstruction of the 3D scene from the real objects. The main challenges faced by the holographic 3D display were introduced, including limited generation speed and accuracy of the computer-generated holograms, the imperfect performance of the holographic display system. In this research, we generated more effective and accurate point cloud data by developing a 3D saliency detection model in the acquisition module. Object points categorized into depth girds with identical depth values in the red, green, and blue (RGB) channels. In each channel, the depth girds are segmented into M × N parts, and only the effective area of the depth grids will be calculated. Computer-generated holograms (CGHs) are generated from efficient depth grids by using Fast Fourier transform (FFT). Compared to the wave-front recording plane (WRP) and traditional PCG methods, the computational complexity is dramatically reduced. The feasibility of the proposed approaches is established through experiments.

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“…The light ray field, which can produce multiple view images with parallax, is a practical and commercialized way for both stereoscopic and auto-stereoscopic 3D displays [ 12 , 13 ]. Benefiting from 3D imaging, hologram synthesis, which sometimes combines the wavefront-based and ray-based light field techniques, can make a hologram of the real world 3D scene under incoherent illumination, making holographic 3D display more realizable [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

3D Imaging Based on Depth Measurement Technologies

Zuo

Lam

et al. 2018

Sensors

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Three-dimensional (3D) imaging has attracted more and more interest because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between the ray-based and wavefront-based 3D imaging techniques.

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Depth-layer weighted prediction method for a full-color polygon-based holographic system with real objects

Cited by 22 publications

References 15 publications

Rapeseed Seed Coat Color Classification Based on the Visibility Graph Algorithm and Hyperspectral Technique

Rapeseed Seed Coat Color Classification Based on the Visibility Graph Algorithm and Hyperspectral Technique

Implementation of a full-color holographic system using RGB-D salient object detection

3D Imaging Based on Depth Measurement Technologies

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