Extensions to Permutation Warping for Parallel Volume Rendering

volume visualization, parallel algorithms © Copyright Hewlett-Packard Company 1998 Biomedical volume visualization requires high quality and high performance, but the existing high performance solutions such as the Shear Warp algorithm, 3D texture mapping, and special purpose hardware have problems. Permutation warping achieves high fidelity for biomedical datasets of regular rectilinear volumes, using a one-to-one communication scheme for optimal O(1) communication on massively parallel computers. Extensions are presented including data dependent optimizations using octrees, arbitrary view angles flexibility, and multiple instruction stream multiple data stream (MIMD) implementation. A MasPar MP-2, single instruction stream multiple data stream (SIMD) (16,384 processor), implementation achieves 14 frames/second, using trilinear reconstruction on 128 3 volumes for 400 % runtime improvement over our previous result. A Proteus MIMD (32 processor) implementation achieves 1 frame/second on the same data. Additionally the PermWeb software architecture is presented, that has shown as a proof of concept means to provide wide shared access to a powerful centralized rendered. All of these improvements make permutation warping an effective solution for biomedical volume visualization

Cache Tiling for High Performance Morphological Image Processing

Morphological image analysis is a technique of processing images through shape characteristics (Jain 1989). Because images are regular data structures morphology algorithm's memory access patterns are predictable. By using read and write patterns, we derive a model of processing to examine inefficiencies for cache processing. We then develop a cache architecture for windowed processing that reduces cache thrashing. Our caching technique, cache tiling, allows dramatic improvement in caching efficiency for small caches independent of compiler optimizations. Programs are not affected providing a transparent solution to improve caching. System code, compilers, or profiling programs can determine the blocking necessary for the best performance. An analytical model for morphological processing memory characteristics is presented which provides for exact cache analysis and prediction. The analytical model is compared to address traces to validate the model. Other algorithms such as inner prod..

Irregular grid volume rendering with composition networks

Volumetric irregular grids are the next frontier to conquer in interactive 3D graphics. Visualization algorithms for rectilinear 256 3 data volumes have been optimized to achieve one frame/second to 15 frames/second depending on the workstation. With equivalent computational resources, irregular grids with millions of cells may take minutes to render for a new viewpoint. The state of the art for graphics rendering, PixelFlow, provides screen and object space parallelism for polygonal rendering. Unfortunately volume rendering of irregular data is at odds with the sort last architecture. I investigate parallel algorithms for direct volume rendering on PixelFlow that generalize to other compositing architectures. Experiments are performed on the Nasa Langley fighter dataset, using the projected tetrahedra approach of Shirley and Tuchman. Tetrahedral sorting is done by the circumscribing sphere approach of Cignoni et al. Key approaches include sortfirst on sort-last, world space subdivision by clipping, rearrangeable linear compositing for any view angle, and static load balancing. The new world space subdivision by clipping provides for efficient and correct rendering of unstructured data by using object space clipping planes. Research results include performance estimates on PixelFlow for irregular grid volume rendering. PixelFlow is estimated to achieve 30 frames/second on irregular grids of 300,000 tetrahedra or 10 million tetrahedra per second

Level Comparisons of Direct Volume Rendering Algorithms

metrics, opacity, gradient, surface classification, volume visualization, image quality, uncertainty visualization Direct volume rendering (DVR) algorithms do not generate intermediate geometry to create a visualization. Yet, they produce countless variations in the resulting images. Therefore, comparative studies are essential for objective interpretation. Even though image and data level comparison metrics are available, it is still difficult to compare results because of the numerous rendering parameters and algorithm specifications involved. Most of the previous comparison methods use information from final rendered images only. We overcome limitations of image level comparisons with our data level approach using intermediate rendering information. We provide a list of rendering parameters and algorithm specifications to guide comparison studies. We extend Williams and Uselton's rendering parameter list with algorithm specification items and provide guidance on how to compare algorithms. Real data are often too complex to study algorithm variations with confidence. Most of the analytic test data sets reported are often useful only for a limited feature of DVR algorithms. We provide simple and easily reproducible test data sets, a checkerboard and a ramp, that can make clear differences in a wide range of algorithm variations. With data level metrics, our test data sets make it possible to perform detailed comparison studies. A number of examples illustrate how to use these tools

Coding Of Spectrally Homogeneous Regions In Multispectral Image Compression

In this paper we present a new approach in the compression of multispectral images. It is based on the merging of two main tendencies such as the use of KLT as a spectral decorrelator and object based image coding schemes. The use of the principal component in multispectral imagery is described and used to perform a multispectral segmentation. This segmentation is taken as the basis for a specific spectral decorrelation for each segmented class. The resulting eigen images present lower variance than classical KLT approaches. Each of the eigen regions is coded spatially using a shape adaptive DCT algorithm. The method outperforms non-region multispectral KLT+DCT schemes as well as JPEG, while adding the region based functionalities. 1. INTRODUCTION Multispectral image compression has for many years been a topic of interest to image processing and remote sensing researchers. From the image processing point of view it is a challenging field, where one faces trade-offs between data size,..