Range image compression.

Abstract

Range Images, which are a representation of the surface of a 3-D object, are gaining popularity in many applications including CAD/CAM, multimedia and virtual reality. There is, thus, a need for compression of these 3-D images. Current standards for still image compression, such as JPEG, are not appropriate for such images because they have been designed specifically for intensity images. This has led us to develop a new compression method for range images. It first scans the image so that the pixels are arranged into a sequence. It then approximates this sequence by straight line segments within a user-specified maximum tolerance level. The extremities of the straight-line segments within a user-specified maximum tolerance level. The extremities of the straight-line segments are non-redundant points (NRPs). Huffman coding, with a fixed Huffman tree, is used to encode the distance between NRPs and their altitudes. A plane-filling scanning technique, known as Peano scanning, is used to improve performance. The algorithms performance is assessed on range images acquired from the Institute for Information Technology of the National Research Council of Canada. The proposed method performs better than JPEG for any given maximum tolerance level. The adaptive mode of the algorithm is also presented along with its performance assessment.