Principle of Maximum Entropy for Histogram Transformation and Image Enhancement

Murilo JuchemRicardo Melo BastosGilson A. GiraldiPaulo S.S. Rodrigues

XVI Simpósio Brasileiro de Engenharia de Software - Gramado, RS, Brasil - 2002

In this paper, we present a histogram transformation technique which can be used for image enhancement in 2D images. It is based on the application of the Principle of Maximum Entropy (PME) for histogram modification. Firstly, a PME problem is proposed in the context of the nonextensive entropy and its implicit solution is presented. Then, an iterative scheme is used to get the solution with a desired precision. Finally, we perform a transformation in the intensity values of the input image whichattempts to alter its spatial histogram to match the PME distribution. In the case study we take some examples in order to demonstrate the advantages of the technique as a preprocessing step in an image segmentation pipeline. This work presents an approach to design multi-agent systems (MAS) for enterprise information systems. Both analysis and design models are depicting through extensions of UML. The modeling process is based on the evolution of the development models where the analysis model diagrams are refined in order to specify the design model. The domain agents attributions are defined according the roles assigned for these ones in the use case model. Considering that the agents are entities with specific roles in the multi-agent society it is proposed specialized agents called infrastructure agents to support the infrastructure services required for the system execution.

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