Numerical algorithms for image geometric transformations and applications

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
Zi-Cai LiStephen S Y Liao

Abstract

To facilitate images under the nonlinear geometric transformation T and its inverse transformation T(-1), we have developed numerical algorithms. A cycle conversion T(-1)T of image transformations is said if an image is distorted by a transformation T and then restored back to itself. The combination (CSIM) of splitting-shooting-integrating methods was first proposed in Li for T(-1)T. In this paper other two combinations, CIIM and C I# I M, of splitting integrating methods for T(-1)T are provided. Combination CSIM has been successfully applied to many topics in image processing and pattern recognition. Since combination CSIM causes large greyness errors, it well suited to a few greyness level images, but needs a huge computation work for 256 greyness level images of enlarged transformations. We may instead choose combination CIIM which involves nonlinear solutions. However, the improved combination C I# I M may bypass the nonlinear solutions completely. Hence, both CIIM and C I# I M can be applied to q(q > or = 256) greyness level images of any enlarged transformations. On the other hand, the combined algorithms, CSIM, CIIM, and C I# I M, are applied to several important topics of image processing and pattern recognition: binar...Continue Reading

Citations

Jun 13, 2013·IEEE Transactions on Cybernetics·Huawei TianXuelong Li
Apr 7, 2010·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Zi-Cai LiChing Y Suen

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