Three-bit representation of three-dimensional range data

Karpinsky, Nikolaus; Wang, Yajun; Zhang, Song

doi:10.1364/ao.52.002286

Cited by 11 publications

(5 citation statements)

References 14 publications

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“…An approach that takes advantage of the aforementioned inherent grid-like structure is to encode 3D coordinates within the color pixels of a regular 2D image. One such technique to store 3D data in a 2D image is to use a virtual structured light scanner [10,11,12,13,14,15]. These image-based methods utilize principles of phase-shifting with a virtual camera and virtual projector to create digital 2D encodings of the 3D surface being compressed.…”

Section: Introductionmentioning

confidence: 99%

Depth Range Reduction for 3D Range Geometry Compression

Finley,

Bell

2020

Preprint

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Three-dimensional (3D) shape measurement devices and techniques are being rapidly adopted within a variety of industries and applications. As acquiring 3D range data becomes faster and more accurate it becomes more challenging to efficiently store, transmit, or stream this data. One prevailing approach to compressing 3D range data is to encode it within the color channels of regular 2D images. This paper presents a novel method for reducing the depth range of a 3D geometry such that it can be stored within a 2D image using lower encoding frequencies (or a fewer number of encoding periods). This allows for smaller compressed file sizes to be achieved without a proportional increase in reconstruction errors. Further, as the proposed method occurs prior to encoding, it is readily compatible with a variety of existing image-based 3D range geometry compression methods.

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Section: Introductionmentioning

confidence: 99%

Depth Range Reduction for 3D Range Geometry Compression

Finley,

Bell

2020

Preprint

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“…The quality of the pattern based on optimization method is higher than that of other methods, and the genetic method improves the phase drastically. However the dithering techniques are originally developed for global similarity [16,17].…”

Section: Introductionmentioning

confidence: 99%

High-quality binary fringe patterns generation by combining optimization on global and local similarity

Lu¹,

Wu²,

Yang³

2018

J. Eur. Opt. Soc.-Rapid Publ.

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Background: The recently proposed optimized dithering techniques can improve measurement quality. However, the objective function in these optimization methods just qualifies the global similarity of the pattern while the global optimization methods ignore the influences of local structure. Method: In order to get high quality binary dithered patterns, this paper presents an algorithm which combines optimization on global and local similarity and implements it in the whole-fringe optimization. Results: Both the simulation and experimental results demonstrate that the proposed algorithm can achieve binary fringe patterns with higher phase quality and less intensity difference. The fringe patterns based on the proposed method can get high quality measurement results. Conclusion: The proposed method can get high quality binary dithered patterns under different defocusing levels by combining global similarity and local structure similarity. The proposed method can improve the robustness to the amounts of defocusing.

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“…Karpinsky et al [29] proposed a method which encoded 3D geometry into three color channels and then performed dithering on each one. Using this method, each 8-bit channel could be represented with a single bit per pixel, allowing all three color channels to be represented with only three bits per pixel.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional range geometry compression via phase encoding

et al. 2017

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One of the state-of-the-art methods for three-dimensional (3D) range geometry compression is to encode 3D data within a regular 24-bit 2D color image. However, most existing methods use all three color channels to solely encode 3D data, leaving no room to store other information (e.g., texture) within the same image. This paper presents a novel method which utilizes geometric constraints, inherent to the structured light 3D scanning device, to reduce the amount of data that need be stored within the output image. The proposed method thus only requires two color channels to represent 3D data, leaving one channel free to store additional information (such as a texture image). Experimental results verify the overall robustness of the proposed method. For example, a compression ratio of 3038:1 can be achieved, versus the STL format, with a root-mean-square error of 0.47% if the output image is compressed with JPEG 80%.

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Three-bit representation of three-dimensional range data

Cited by 11 publications

References 14 publications

Depth Range Reduction for 3D Range Geometry Compression

Depth Range Reduction for 3D Range Geometry Compression

High-quality binary fringe patterns generation by combining optimization on global and local similarity

Three-dimensional range geometry compression via phase encoding

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