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2018 | OriginalPaper | Buchkapitel

Combining Diffusion Filter Algorithms with Super—Resolution for Abnormality Detection in Medical Images

verfasst von : Shilpa Joshi, R. K. Kulkarni

Erschienen in: Computational Vision and Bio Inspired Computing

Verlag: Springer International Publishing

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Abstract

One of the most significant areas of image research is Image Enhancement. The main aspect of image enhancement involves the improvisation of the visual manifestation of an image. Poor contrast and noise affect many kinds of images today, such as satellite images, remote sensing images, medical images, real-life images and electron microscope images. Therefore, noise removal and resolution increment are important as well as necessary to ensure and enhance the quality of images. There are many imaging modalities and each of them performs different functions ranging from the provision of information about human anatomy/structure to the provision of location statistics about specific activities and tasks. Physical constraints of system detectors—which are tuned to signal-to-noise and timing considerations are used to determine the resolution of imaging systems. The hybrid techniques designed n this paper uses algorithms are mostly based on standard diffusion filters and SR algorithms. Results demonstrate the potential in introducing SR techniques into practical medical applications.

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Vorheriges Kapitel Histogram Modification and Bi-level Moment Preservation Based Reversible Watermarking
Nächstes Kapitel Design of an Algorithm for People Identification Using Facial Descriptors
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Metadaten
Titel
Combining Diffusion Filter Algorithms with Super—Resolution for Abnormality Detection in Medical Images
verfasst von
Shilpa Joshi
R. K. Kulkarni
Copyright-Jahr
2018
Buch
Computational Vision and Bio Inspired Computing

Print ISBN: 978-3-319-71766-1

Electronic ISBN: 978-3-319-71767-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-71767-8_95

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