DocumentCode :
861350
Title :
Footprint area sampled texturing
Author :
Chen, Baoquan ; Dachille, Frank ; Kaufman, Arie E.
Author_Institution :
Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA
Volume :
10
Issue :
2
fYear :
2004
Firstpage :
230
Lastpage :
240
Abstract :
We study texture projection based on a four region subdivision: magnification, minification, and two mixed regions. We propose improved versions of existing techniques by providing exact filtering methods which reduce both aliasing and overblurring, especially in the mixed regions. We further present a novel texture mapping algorithm called FAST (footprint area sampled texturing), which not only delivers high quality, but also is efficient. By utilizing coherence between neighboring pixels, performing prefiltering, and applying an area sampling scheme, we guarantee a minimum number of samples sufficient for effective antialiasing. Unlike existing methods (e.g., MlP-map, Feline), our method adapts the sampling rate in each chosen MlP-map level separately to avoid undersampling in the lower level l for effective antialiasing and to avoid oversampling in the higher level l+1 for efficiency. Our method has been shown to deliver superior image quality to Feline and other methods while retaining the same efficiency. We also provide implementation trade offs to apply a variable degree of accuracy versus speed.
Keywords :
antialiasing; filtering theory; image resolution; image sampling; image texture; anisotropic filtering; antialiasing; backward mapping; footprint area sampling; forward mapping; image quality; region subdivision; texture mapping algorithm; Anisotropic filters; Computer Society; Filtering; Hardware; Image generation; Image quality; Image sampling; Pixel; Sampling methods; Shape; Algorithms; Computer Graphics; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sample Size; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2004.1260775
Filename :
1260775
Link To Document :
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