IEEE Computer Graphics and Applications
A fast algorithm for general raster rotation
Proceedings on Graphics Interface '86/Vision Interface '86
Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
Fundamentals of digital image processing
Fundamentals of digital image processing
Filters for common resampling tasks
Graphics gems
Footprint evaluation for volume rendering
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Three-pass affine transforms for volume rendering
VVS '90 Proceedings of the 1990 workshop on Volume visualization
Feature-based image metamorphosis
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Frequency domain volume rendering
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
ACM Transactions on Graphics (TOG)
Reconstruction filters in computer-graphics
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Constant-time filtering with space-variant kernels
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Multirate Digital Signal Processing
Multirate Digital Signal Processing
Principles of Digital Image Synthesis
Principles of Digital Image Synthesis
Digital Image Warping
Multidimensional Digital Signal Processing
Multidimensional Digital Signal Processing
Frequency Analysis of Gradient Estimators in Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Clamping: A method of antialiasing textured surfaces by bandwidth limiting in object space
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
3-D transformations of images in scanline order
SIGGRAPH '80 Proceedings of the 7th annual conference on Computer graphics and interactive techniques
Optimal filter design for volume reconstruction and visualization
VIS '93 Proceedings of the 4th conference on Visualization '93
An evaluation of reconstruction filters for volume rendering
VIS '94 Proceedings of the conference on Visualization '94
Proceedings of the 1996 symposium on Volume visualization
A comparison of normal estimation schemes
VIS '97 Proceedings of the 8th conference on Visualization '97
Design of accurate and smooth filters for function and derivative reconstruction
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Structured spatial domain image and data comparison metrics
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Reducing aliasing artifacts in iso-surfaces of binary volumes
VVS '00 Proceedings of the 2000 IEEE symposium on Volume visualization
Mastering windows: improving reconstruction
VVS '00 Proceedings of the 2000 IEEE symposium on Volume visualization
Evaluation and Design of Filters Using a Taylor Series Expansion
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Evaluation of Image Quality in Medical Volume Visualization: The State of the Art
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Ray-Based Data Level Comparisons of Direct Volume Rendering Algorithms
Dagstuhl '97, Scientific Visualization
Visualization in Medicine: Theory, Algorithms, and Applications
Visualization in Medicine: Theory, Algorithms, and Applications
Truncation Error Estimate on Random Signals by Local Average
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
A perceptual framework for comparisons of direct volume rendered images
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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Reconstruction is prerequisite whenever a discrete signal needs to be resampled as a result of transformation such as texture mapping, image manipulation, volume slicing, and rendering. We present a new method for the characterization and measurement of reconstruction error in spatial domain. Our method uses the Classical Shannon's Sampling Theorem as a basis to develop error bounds. We use this formulation to provide, for the first time, an efficient way to guarantee an error bound at every point by varying the size of the reconstruction filter. We go further to support position-adaptive reconstruction and data-adaptive reconstruction which adjust filter size to the location of reconstruction point and to the data values in its vicinity. We demonstrate the effectiveness of our methods with 1D signals, 2D signals (images), and 3D signals (volumes).