Feature-preserving Quantization for 3D Seismic Visualization
Seismic volume datasets are usually obtained in 32-bit floating point precision, which makes them difficult to be processed on commodity computer due to their large size and high dynamic range (HDR). In this paper, we present a novel quantization method which not only compresses the size of seismic datasets, but also preserves the important seismic features such as detailed structures, local relevance structures and singularities. Our method first identifies the subrange of detailed structures by measuring the differ- ence between the histograms of original datasets and those smoothed by bilateral filter. Then, local relevance statistics (LRS) is proposed to determine subranges of local relevance structures. We also assign relatively small subranges for pre- serving some indispensable singularities. According to the piecewise coordinates, our feature-preserving quantization technique is conducted and the low dynamic range(LDR) datasets are generated. To further preserve the local contrast and keep the continuity of original datasets, tone reduction and Bezier curve are resorted to optimize our quantization process. As will be shown in the comparative study, our quantified LDR datasets could be easily rendered on normal graphic hardwares, and the rendering results still present the features of interest, which facilitate further seismic interpretations.
国际会议
2011国际计算机辅助设计与图形学学术会议(CAD/Graphics 2011)
济南
英文
1-10
2011-09-15（万方平台首次上网日期，不代表论文的发表时间）