Paper
25 August 2006 On the development of a high-order texture analysis using the PWD and Renyi entropy
S. Gabarda, G. Cristóbal
Author Affiliations +
Abstract
Renyi entropy, used as a data analysis tool, brings a helpful information in many practical applications, due to its relevant properties when dealing with time or space-frequency representations (TFR or SFR). It's characterized for providing generalized information content (entropy) of a given signal under a local constraint. This paper deals with the problem of discriminating isotrigon patterns against binary random backgrounds and it is extended also to deal with the multi-texture isotrigon case. Discrimination is performed through a suitable Renyi entropy normalization, extracted from a spatially oriented 1-D pseudo-Wigner distributions (PWD) of the test images. A previous step is carried out by substituting the original patterns by their respective localized spatially oriented Allan variances. In this way, discrimination can be improved through the anisotropic behavior shown by the Allan variance of the patterns. The method has been empirically evaluated using a family of isotrigon patterns embedded in a binary random background and also for the multiple isotrigon mosaics case and compared with other existing methods.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Gabarda and G. Cristóbal "On the development of a high-order texture analysis using the PWD and Renyi entropy", Proc. SPIE 6313, Advanced Signal Processing Algorithms, Architectures, and Implementations XVI, 63130V (25 August 2006); https://doi.org/10.1117/12.682135
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KEYWORDS
Binary data

Image segmentation

Data analysis

Image processing

Anisotropy

Image information entropy

Performance modeling

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