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Pharmaceuticals used to treat nervousness (antianxiety drugs) and induce sleep (sedatives or sleep aids) may cause dependence. These medication embrace benzodiazepines (reminiscent of diazepam and lorazepam ) and barbiturates. Each  legal amphetamines ([http://www.legaldrugsforsale.com http://www.legaldrugsforsale.com]) works differently, and each has a distinct potential for dependency and tolerance.<br><br>As our nation has come to rely more closely on pharmaceutical medicine to manage  power ache and [http://Photobucket.com/images/psychological psychological] well being, the U.S. army has followed go well with, doling out drugs on the battlefield and now again on the house entrance in an enormous network of veterans (VA) hospitals and clinics. However as the charges of sudden dying and suicide have spiked over the past decade, it is turn into clearer to mental well being and army advocates that this heavy reliance on prescription drugs may be partly in charge.<br><br>Data in the Nationwide Prescription Audit (NPA) is derived from IMS Well being's Xponent service, one of the full, [http://www.Sharkbayte.com/keyword/nationwide-level nationwide-level] prescription databases in the U.S. Xponent captures roughly 70% Market Share of all prescriptions in the U.S. IMS then makes use of a patented projection methodology from a stratified and geographically balanced sample to symbolize 100% Market Share protection of U.S. prescription exercise at retail, mail service, long-time period care, and managed care retailers. <br><br>Benzodiazepines are central nervous system depressants that may produce pleasurable feelings of rest and sedation. Because drugs like Xanax act shortly, they are often taken to head off an episode of intense nervousness. But the longer you depend on benzodiazepines to manage your symptoms, the extra susceptible you're to drug dependence. If you end up rising agitated when you may't take your dose of hysteria remedy, otherwise you need more and more large doses to alleviate your signs, you may be growing a dependence on a prescription drug. Utilizing Prescription Medicine to Self-Medicate<br><br>Xanax is a testomony to the potential of psychiatric medicines to transform our society. Our record of the most well-liked psychiatric drugs, which relies on 2009 prescription data provided by the pharmacy knowledge experts at IMS Well being , offers a deep look into the mind-altering medicines which have modified the way we live. For decades some doctors have complained these drugs are overused for delicate temper issues. While drug companies are slicing again analysis into new psychiatric drugs, docs still prescribe psychiatric medication more than 250 million occasions each year.<br><br>If your nervousness symptoms aren't attributable to a medical situation, then evaluation the stressors in your life. Chances are you'll be reacting to being over-tired, anxious or afraid of something happening in your job or household. If this is the case, the symptoms may very effectively finish when the stress factors do. If you really feel you may want some assist in coping while going via it then see your doctor.Some kinds of anxiety are readily controlled by drugs (typically known as anti-anxiousness drugs or mood stabilizers), which may be prescribed and monitored by a psychiatrist.
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 15:57, 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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