Two-channel 3D range geometry compression with primitive depth modification. (March 2022)

• Record Type: Journal Article
• Authors: Finley, Matthew G.; Bell, Tyler
• Is Part Of: Optics and lasers in engineering. Volume 150(2022)
• Publication Date: 2022-03
• Subjects: 3D range data compression -- Depth encoding -- Depth modification -- Range image processing -- Phase unwrapping; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2021.106832
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlights: Novel method to encode 3D range data within only two channels of an RGB image. Enabled by modifying the 3D range data with a geometric primitive prior to encoding. Removal of the third color channel enables significant file size savings. Able to maintain very high global RMS reconstruction accuracy. Compatible with both lossless and lossy image compression formats. Abstract: Modern computing and imaging technologies have allowed for many recent advances to be made in the field of 3D range imaging: range data can now be acquired at speeds much faster than real-time, with sub-millimeter precision. However, these benefits come at the cost of an increased quantity of data being generated by 3D range imaging systems, potentially limiting the number of applications that can take advantage of this technology. One common approach to the compression of 3D range data is to encode it within the three color channels of a traditional 24-bit RGB image. This paper presents a novel method for the modification and compression of 3D range data such that the original depth information can be stored within, and recovered from, only two channels of a traditional 2D RGB image. Storage within a traditional image format allows for further compression to be realized via lossless or lossy image compression techniques. For example, when JPEG 80 is used to store the encoded output image, this method achieves an 18.2% reduction in file size when compared to a similar three-channel, image-base compression method, with only a corresponding 0.17% reduction in global reconstruction accuracy.