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.

© 2020 Optical Society of America

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