Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/19681
Title: Spectral unmixing of mixed pixels for texture boundary refinement
Authors: Camilleri, Kenneth P.
Petrou, Maria
Keywords: Signal processing
Speech processing systems
Image segmentation
Parameter estimation
Issue Date: 2000
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Camilleri, K. P., & Petrou, M. (2000). Spectral unmixing of mixed pixels for texture boundary refinement. 15th International Conference on Pattern Recognition (ICPR-2000), Barcelona. 1084-1087.
Abstract: 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 relabelled according to the region distribution which contributes most to that pixel, thus refining the region boundaries.
URI: https://www.um.edu.mt/library/oar//handle/123456789/19681
Appears in Collections:Scholarly Works - FacEngSCE

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