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In [[mathematical morphology]] and [[digital image processing]], '''top-hat transform''' is an operation that extracts small elements and details from given [[image]]s. There exist two types of top-hat transform: The ''white top-hat transform'' is defined as the difference between the input image and its [[opening (morphology)|opening]] by some [[structuring element]]; The ''black top-hat transform'' is defined dually as the difference between the [[closing (morphology)|closing]] and the input image. Top-hat transforms are used for various image processing tasks, such as [[feature extraction]], [[background equalization]], [[image enhancement]], and others. | |||
==Mathematical definitions== | |||
Let <math>f:E\mapsto R</math> be a [[grayscale]] image, mapping points from an [[Euclidean space]] or discrete [[Lattice graph|grid]] ''E'' (such as ''R''<sup>2</sup> or ''Z''<sup>2</sup>) into the real line. Let <math>b(x)</math> be a grayscale structuring element. | |||
Then, the white top-hat transform of ''f'' is given by: | |||
:<math>T_w(f)=f-f \circ b</math>, | |||
where <math>\circ</math> denotes the opening operation. | |||
The black top-hat transform of ''f'' (sometimes called the ''bottom-hat'' transform<ref>{{Cite web|last=Tcheslavski|first=Gleb V.|url=http://www.ee.lamar.edu/gleb/dip/10-3%20-%20Morphological%20Image%20Processing.pdf|title=Morphological Image Processing: Gray-scale morphology|year=2010|accessdate=4 November 2013}}</ref> | |||
) is given by: | |||
:<math>T_b(f)=f\bullet b-f</math>, | |||
where <math>\bullet</math> is the closing operation. | |||
==Properties== | |||
The white top-hat transform returns an image, containing those "objects" or "elements" of an input image that: | |||
* Are "smaller" than the structuring element (i.e., places where the structuring element does not fit in), and | |||
* are '''brighter''' than their surroundings. | |||
The black top-hat returns an image, containing the "objects" or "elements" that: | |||
* Are "smaller" than the structuring element, and | |||
* are '''darker''' than their surroundings. | |||
The size, or width, of the elements that are extracted by the top-hat transforms can be controlled by the choice of the structuring element <math>b</math>. The bigger the latter, the larger the elements extracted. | |||
Both top-hat transforms are images that contain only non-negative values at all pixels. | |||
==References== | |||
* <cite id=serra82>''Image Analysis and Mathematical Morphology'' by Jean Serra, ISBN 0-12-637240-3 (1982)</cite> | |||
* ''Image Analysis and Mathematical Morphology, Volume 2: Theoretical Advances'' by Jean Serra, ISBN 0-12-637241-1 (1988) | |||
* ''An Introduction to Morphological Image Processing'' by Edward R. Dougherty, ISBN 0-8194-0845-X (1992) | |||
* ''Hands-on Morphological Image Processing'' by Edward R. Dougherty and R. Lotufo, ISBN 0-8194-4720-X (2003) | |||
{{reflist}} | |||
[[Category:Mathematical morphology]] | |||
[[Category:Digital geometry]] | |||
{{compu-graphics-stub}} | |||
{{comp-sci-stub}} |
Revision as of 14:57, 13 January 2014
In mathematical morphology and digital image processing, top-hat transform is an operation that extracts small elements and details from given images. There exist two types of top-hat transform: The white top-hat transform is defined as the difference between the input image and its opening by some structuring element; The black top-hat transform is defined dually as the difference between the closing and the input image. Top-hat transforms are used for various image processing tasks, such as feature extraction, background equalization, image enhancement, and others.
Mathematical definitions
Let be a grayscale image, mapping points from an Euclidean space or discrete grid E (such as R2 or Z2) into the real line. Let be a grayscale structuring element.
Then, the white top-hat transform of f is given by:
where denotes the opening operation.
The black top-hat transform of f (sometimes called the bottom-hat transform[1] ) is given by:
where is the closing operation.
Properties
The white top-hat transform returns an image, containing those "objects" or "elements" of an input image that:
- Are "smaller" than the structuring element (i.e., places where the structuring element does not fit in), and
- are brighter than their surroundings.
The black top-hat returns an image, containing the "objects" or "elements" that:
- Are "smaller" than the structuring element, and
- are darker than their surroundings.
The size, or width, of the elements that are extracted by the top-hat transforms can be controlled by the choice of the structuring element . The bigger the latter, the larger the elements extracted.
Both top-hat transforms are images that contain only non-negative values at all pixels.
References
- Image Analysis and Mathematical Morphology by Jean Serra, ISBN 0-12-637240-3 (1982)
- Image Analysis and Mathematical Morphology, Volume 2: Theoretical Advances by Jean Serra, ISBN 0-12-637241-1 (1988)
- An Introduction to Morphological Image Processing by Edward R. Dougherty, ISBN 0-8194-0845-X (1992)
- Hands-on Morphological Image Processing by Edward R. Dougherty and R. Lotufo, ISBN 0-8194-4720-X (2003)
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