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Sociedade Brasileira de Telecomunicações

Context Selection for Lossless Compression of Bi-Level Images

Bi-level images are used in many fields to represent binary masks for object and region of interest coding, enhancement layers of color images and point cloud occupancy maps as geometry slices. Compression of bi-level images is usually performed using context adaptive arithmetic coding. In this paper, we propose a low complexity context selection algorithm that chooses, for each image being encoded, the most useful contexts for encoding that particular image. This information is then transmitted in the bitstream at the cost of 16 bits. Results show that the proposed algorithm outperforms the typical, fixed contexts for natural images and, by a larger margin, for point cloud geometry slices.

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