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Global support radial base functions are effective in eliminating impulsive noise in non-linear processing. This paper introduces an interpolation technique which efficiently reduces image impulsive noise by means of an interpolant obtained through radial base functions. These functions have been used in a research project designed to develop a system for the recovery of images of Amazonian aquatic resources. This technique starts with the tagging by interpolation of noisy image pixels. Thus, a value of reconstruction for the noisy pixels is generated using neighboring pixels. The results obtained with this technique have proved comparable and often better than those obtained with previously known techniques. According to results analysis, this technique can be successfully applied on images with high noise levels. The results are low error in noisy pixel reconstruction and better visual quality. [ABSTRACT FROM AUTHOR]

In Information Retrieval Systems, Image Retrieval Systems are located; they allow generating searching and storing processes of resources through coincidences by key words or other real-time methods. This type of systems can use visual content of images (color, texture, and brightness) as indices. In addition, these systems combine different attributes to improve the processes of classification and relevance of the searching process results known as "Information Quality." This paper presents the modeling of a Image Retrieval System which combines attributes of the contentbased retrieval such as color, texture, and shape, with the Information Quality-based retrieval as updating portability and relevance frequency in the context of Digital Image Collection of Aquatic Amazon Ecosystems of Universidad del Amazonia CAPREA Research Group. [ABSTRACT FROM AUTHOR]