This paper presents a novel wavelet-based transform and coding scheme for irregular meshes. The transform preserves geometric features at lower resolutions by adaptive vertex sampling and retriangulation, resulting in more accurate subsampling and better avoidance of smoothing and aliasing artefacts. By employing octree-based coding techniques, the encoding of both connectivity and geometry information is decoupled from any mesh traversal order, and allows for exploiting the intra-band statistical dependencies between wavelet coefficients. Improvements over the state of the art obtained by our approach are three-fold:(1) improved rate-distortion performance over Wavemesh and IPR for both the Hausdorff and root mean square distances at low-to-mid-range bitrates, most obvious when clear geometric features are present while remaining competitive for smooth, feature-poor models; (2) improved rendering performance at any triangle budget, translating to a better quality for the same runtime memory footprint; (3) improved visual quality when applying similar limits to the bitrate or triangle budget, showing more pronounced improvements than rate-distortion curves.

We introduce a novel functionality for wavelet-based irregular mesh codecs which allows for prioritizing at the encoding side a region-of-interest (ROI) over a background (BG), and for transmitting the encoded data such that the quality in these regions increases first. This is made possible by appropriately scaling wavelet coefficients. To improve the decoded geometry in the BG, we propose an ROI-aware inverse wavelet transform which only upscales the connectivity in the required regions. Results show clear bitrate and vertex savings. For a trivial front-back selection of the ROI and BG, rendering from the front saves up to 5 bits per vertex and up to 50% of the geometry, while appearing visually lossless.

Abstract:This work investigates the optimization of mesh quality at lossy rates for a lossless scalable wavelet-based irregular mesh codec. Whereas previously proposed wavelet-based irregular mesh codecs offer coarse-grain resolution scalability, in this paper we propose a coding scheme which enables fine-grain quality scalability. This is done by avoiding the use of geometric data in the encoding process, which reduces dependencies within the data stream and allows for an unrestricted storage and transmission order of wavelet subband bitplanes and connectivity information. This in turn allows us to perform rate-distortion optimization, whereby the subband bitplanes to be encoded are determined by minimizing distortion subject to an overall target bitrate. Experimental results show that the proposed coding approach offers fine-grain quality scalability, achieves optimality in rate-distortion sense and improves compression performance over the state of the art.