Medical Image Enhancement using Logarithmic Image Processing

E. Zaharescu (Romania)


Medical imagery, image enhancement, logarithmic image processing, real vector space, Euclidean space. 1.


The logarithmic image processing theory is a mathematical framework that provides a set of specific algebraic and functional operations and structures that are well adapted to the representation and processing of non linear images, and more generally of non-linear signals, valued in a bounded intensity range. The purpose of this paper is to introduce a new mathematical LIP model focused on theoretical and practical aspects concerning the enhancement of the transmitted medical images and the physical absorption/transmission laws expressed within LIP mathematical framework. First of all the bounded interval (-1,1) is considered as the set of gray levels and we define two operations: addition 〈+〉 and real scalar multiplication 〈x〉. With these operations, the set of gray levels becomes a real vector space. Then, defining the scalar product (.|.) and the norm || .|| , we obtain an Euclidean space of the gray levels. Secondly, we extend these operations and functions for color images. Finally, the experimental results, shown as enhanced medical images, reveal that this method has wide potential areas of impact which may include: Digital X ray, Digital Mammography, Computer Tomography Scans, Nuclear Magnetic Resonance Imagery and Telemedicine Applications.

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