Journal Paper

"Two-channel 3D range geometry compression with primitive depth modification." Optics and Lasers in Engineering (2022)

M. G. Finley, T. Bell, “Two-channel 3D range geometry compression with primitive depth modification,” Optics and Lasers in Engineering, Volume 150:106832 (2022)

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.

"Variable precision depth encoding for 3D range geometry compression," Appl. Opt. (2020)

M.G. Finley, J.Y. Nishimura, and T. Bell, “Variable precision depth encoding for 3D range geometry compression,” Appl. Opt., 59(17), 5290-5299, 2020.

Abstract

State-of-the-art 3D range geometry compression algorithms that utilize principles of phase shifting perform encoding with a fixed frequency; therefore, it is not possible to encode individual points within a scene at various degrees of precision. This paper presents a novel, to the best of our knowledge, method for accurately encoding 3D range geometry within the color channels of a 2D RGB image that allows the encoding frequency—and therefore the encoding precision—to be uniquely determined for each coordinate. The proposed method can thus be used to balance between encoding precision and file size by encoding geometry along a statistical distribution. For example, a normal distribution allows for more precise encoding where the density of data is high and less precise encoding where the density of data is low. Alternative distributions may be followed to produce encodings optimized for specific applications. In general, the nature of the proposed encoding method enables the precision to be freely controlled at each point or centered around identified features of interest, ideally enabling this method to be used within a wide range of applications.

"Two-channel depth encoding for 3D range geometry compression," Appl. Opt. (2019)

M.G. Finley and T. Bell, "Two-channel depth encoding for 3D range geometry compression," Appl. Opt. 58(25), 6882-6890 (2019). (Cover Feature)

Abstract

This paper presents a novel method for accurately encoding 3D range geometry within only two channels of a 2D RGB image using a two-frequency phase-shifting approach. Once encoded within a 2D image, 3D geometry can be further compressed with conventional lossless or lossy image compression methods. The nature of the proposed two-channel encoding is relatively smooth; thus, large compression ratios with high reconstruction accuracies can be achieved and are experimentally demonstrated. For example, a compression ratio of 2883:1 was achieved, compared with the STL format, with a reconstruction RMS error of 0.45 mm (99.8% accuracy) when JPEG 85 was used with the proposed method. This paper also demonstrates how a 24-bit color texture map can be encoded alongside 3D geometry within a single 2D image.