Morphological Enhancement of Medical Images in a Logarithmic Image Environment

Zaharescu, Eugen

doi:10.1109/icdsp.2007.4288546

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2019

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“…To address this issue, Jourlin et al [16], [22] have introduced LIP top-hats where the LIP-difference △ − replaces the usual difference "−". Zaharescu [23] proposed variants of LIP top-hats. However, all these top-hats are still defined with a flat structuring element.…”

Section: Top-hat Operatorsmentioning

confidence: 99%

Logarithmic Mathematical Morphology: A New Framework Adaptive to Illumination Changes

Noyel

2019

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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A new set of mathematical morphology (MM) operators adaptive to illumination changes caused by variation of exposure time or light intensity is defined thanks to the Logarithmic Image Processing (LIP) model. This model based on the physics of acquisition is consistent with human vision. The fundamental operators, the logarithmic-dilation and the logarithmic-erosion, are defined with the LIP-addition of a structuring function. The combination of these two adjunct operators gives morphological filters, namely the logarithmic-opening and closing, useful for pattern recognition. The mathematical relation existing between "classical" dilation and erosion and their logarithmic-versions is established facilitating their implementation. Results on simulated and real images show that logarithmic-MM is more efficient on low-contrasted information than "classical" MM.

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Section: Top-hat Operatorsmentioning

confidence: 99%

Logarithmic Mathematical Morphology: A New Framework Adaptive to Illumination Changes

Noyel

2019

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

View full text Add to dashboard Cite

show abstract

Morphological Enhancement of Medical Images in a Logarithmic Image Environment

Cited by 1 publication

References 6 publications

Logarithmic Mathematical Morphology: A New Framework Adaptive to Illumination Changes

Logarithmic Mathematical Morphology: A New Framework Adaptive to Illumination Changes

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