KEYWORDS: 3D modeling, Quantization, Distortion, Visualization, Process modeling, Systems modeling, Binary data, 3D acquisition, 3D image processing, Visual process modeling
In the field of compression, the type of 3D models traditionally considered is that of polygonal meshes, for which several efficient compression techniques have been proposed in the recent years. Nowadays, an increasing proportion of 3D models are created by a synthesis or modeling process, instead of captured from the real world. Such models are most often given as parametric surfaces, which have several advantages over polygonal meshes, such as resolution independence and a more compact representation. This paper proposes a method to code parametric surfaces, given as Non-Uniform Rational B-Splines (NURBS). The coding scheme consists in coding the NURBS parameters (knots and control points) using a predictive scheme, coupled with uniform quantization and entropy coding. The multiplicity of knots is preserved by decomposing the knot vectors in a break vector (the values) and a multiplicity map. The rate-distortion of the proposed scheme is evaluated and compared against compressed triangular meshes. The results show that a considerable compression ratio is achievable under visually lossless conditions, that outperforms by far triangular meshes. In addition of having a better rate-distortion performance, the coding scheme enables the efficient transmission of synthesized 3D models retaining their resolution independence.
Region Of Interest (ROI) coding is one of the innovative functionalities supported by JPEG 2000, the new ISO/ITU-T still image coding standard developed by the Joint Photographic Experts Group (JPEG). It enables a non-uniform distribution of the image quality between a selected region (the ROI) and the rest of the image (background). This feature is obtained by scaling background coefficients in the wavelet domain. According to the ROI Maxshift method defined in JPEG 2000 part 1 (baseline algorithm), the background bit-planes are down-shifted below all ROI coefficients. In addition, the ROI can have any shape as the latter does not need to be transmitted to a JPEG 2000 decoder (no codestream overhead due to the coding of the shape). On the contrary, this method requires decoding of all ROI coefficients before accessing bit-planes of the background. Furthermore, it uses large shifting values that significantly increase the number of total bit-planes to encode. In JPEG 2000 part 2 (extensions), a generic (Scaling based) ROI coding has been included. This method supports any scaling values. In particular, it allows a rough control on both ROI and background qualities distributions in the codestream, but implies the derivation of a ROI bit-mask at the decoding side. This paper starts by providing some hints on how to choose an optimal Maxshift scaling value, as well as how to pad the ROI extra bits appearing during the shift operation. Then, it proposes an encoding algorithm that combines advantages of both ROI methods. This algorithm can be used by applications where visually lossless ROI*s is acceptable and is based on an extension of the Maxshift method to low scaling values. The generated codestreams remain compliant with the Maxshift decoding algorithm described in JPEG 2000 part 1, and can be consequently handled by any JPEG 2000 decoder.
JPEG 2000, the new ISO/ITU-T standard for still image coding, is about to be finished. Other new standards have been recently introduced, namely JPEG-LS and MPEG-4 VTC. This paper compares the set of features offered by JPEG 2000, and how well they are fulfilled, versus JPEG-LS and MPEG-4 VTC, as well as the older but widely used JPEG and more recent PNG. The study concentrates on compression efficiency and functionality set, while addressing other aspects such as complexity. Lossless compression efficiency as well as the fixed and progressive lossy rate-distortion behaviors are evaluated. Robustness to transmission errors, Region of Interest coding and complexity are also discussed. The principles behind each algorithm are briefly described. The results show that the choice of the 'best' standard depends strongly on the application at hand, but that JPEG 2000 supports the widest set of features among the evaluated standards, while providing superior rate-distortion performance in most cases.
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