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15th International Conference on Pattern Recognition (ICPR'00) - Volume 3
Spectral Unmixing of Mixed Pixels for Texture Boundary Refinement
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
Kenneth P. Camilleri, University of Malta
Maria Petrou, University of Surrey
Feature-based texture segmentation methods often compute the texture features over a window of finite support converting raw texture descriptors into usable texture features. However, this process has the adverse effect of blurring the texture feature boundaries such that features at pixels close to the boundaries are a mixture of raw descriptors from two distributions. We propose a method, which gives the least-squares estimate of the proportional mixture of a pixel feature from the two distributions representing the regions on each side of the boundary. In this manner, each pixel may be relabeled according to the region distribution, which contributes most to that pixel, thus refining the region boundaries.
Citation:
Kenneth P. Camilleri, Maria Petrou, "Spectral Unmixing of Mixed Pixels for Texture Boundary Refinement," icpr, vol. 3, pp.7096, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 3, 2000
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