Splitting-integrating method for normalizing images by inverse transformations

The splitting-integrating method is a technique developed for the normalization of images by inverse transformation. It does not require solving nonlinear algebraic equations and is much simpler than any existing algorithm for the inverse nonlinear transformation. Moreover, its solutions have a high...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 1992-06, Vol.14 (6), p.678-686
Main Authors: Li, Z.C., Suen, C.Y., Bui, T.D., Tang, Y.Y., Gu, Q.L.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Filtering
Image converters
Nonlinear distortion
Nonlinear equations
Optical filters
Optical noise
Pattern recognition
Pattern recognition. Digital image processing. Computational geometry
Predistortion
Signal processing algorithms
Speech processing
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Summary:The splitting-integrating method is a technique developed for the normalization of images by inverse transformation. It does not require solving nonlinear algebraic equations and is much simpler than any existing algorithm for the inverse nonlinear transformation. Moreover, its solutions have a high order of convergence, and the images obtained through T/sup -1/ are free from superfluous holes and blanks, which often occur in transforming digitized images by other approaches. Application of the splitting-integrating method can be extended to supersampling in computer graphics, such as picture transformations by antialiasing, inverse nonlinear mapping, etc.< >
ISSN:0162-8828
1939-3539
DOI:10.1109/34.141558