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The Gray-Code Filter Kernels
March 2007 (vol. 29 no. 3)
pp. 382-393
Hagit Hel-Or, IEEE Computer Society
Yacov Hel-Or, IEEE Computer Society
In this paper, we introduce a family of filter kernels—the Gray-Code Kernels (GCK) and demonstrate their use in image analysis. Filtering an image with a sequence of Gray-Code Kernels is highly efficient and requires only two operations per pixel for each filter kernel, independent of the size or dimension of the kernel. We show that the family of kernels is large and includes the Walsh-Hadamard kernels, among others. The GCK can be used to approximate any desired kernel and, as such forms, a complete representation. The efficiency of computation using a sequence of GCK filters can be exploited for various real-time applications, such as, pattern detection, feature extraction, texture analysis, texture synthesis, and more.
Index Terms:
Image filtering, filters, filter kernels, convolution, Walsh-Hadamard, pattern matching, block matching, pattern detection.
Citation:
Gil Ben-Artzi, Hagit Hel-Or, Yacov Hel-Or, "The Gray-Code Filter Kernels," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 3, pp. 382-393, March 2007, doi:10.1109/TPAMI.2007.62
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