Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform

Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with h...

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Published in:	Entropy (Basel, Switzerland) Vol. 21; no. 3; p. 244
Main Authors:	Mello Román, Julio César, Vázquez Noguera, José Luis, Legal-Ayala, Horacio, Pinto-Roa, Diego P, Gomez-Guerrero, Santiago, García Torres, Miguel
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 04-03-2019 MDPI
Subjects:	Algorithms Darkness discrete entropy Entropy Feature extraction Image contrast Image enhancement Information theory Infrared imagery infrared images Light low contrast Morphology multiscale top-hat transform Radiation Random variables Visual perception discrete entropy infrared images multiscale top-hat transform low contrast
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Abstract	Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception. These problems can be caused by variations of the environment or by limitations of the cameras that capture the images. In this work we propose a method that improves the details of infrared images, increasing their entropy, preserving their natural appearance, and enhancing contrast. The proposed method extracts multiple features of brightness and darkness from the infrared image. This is done by means of the multiscale top-hat transform. To improve the infrared image, multiple scales are added to the bright areas and multiple areas of darkness are subtracted. The method was tested with 450 infrared thermal images from a public database. Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.
AbstractList	Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception. These problems can be caused by variations of the environment or by limitations of the cameras that capture the images. In this work we propose a method that improves the details of infrared images, increasing their entropy, preserving their natural appearance, and enhancing contrast. The proposed method extracts multiple features of brightness and darkness from the infrared image. This is done by means of the multiscale top-hat transform. To improve the infrared image, multiple scales are added to the bright areas and multiple areas of darkness are subtracted. The method was tested with 450 infrared thermal images from a public database. Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.
Author	García Torres, Miguel Gomez-Guerrero, Santiago Mello Román, Julio César Vázquez Noguera, José Luis Pinto-Roa, Diego P Legal-Ayala, Horacio
AuthorAffiliation	1 Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay 2 Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain
AuthorAffiliation_xml	– name: 1 Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – name: 2 Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain
Author_xml	– sequence: 1 givenname: Julio César orcidid: 0000-0002-3698-4043 surname: Mello Román fullname: Mello Román, Julio César organization: Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – sequence: 2 givenname: José Luis orcidid: 0000-0002-9766-4182 surname: Vázquez Noguera fullname: Vázquez Noguera, José Luis organization: Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – sequence: 3 givenname: Horacio orcidid: 0000-0002-1790-2559 surname: Legal-Ayala fullname: Legal-Ayala, Horacio organization: Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – sequence: 4 givenname: Diego P orcidid: 0000-0003-2479-9876 surname: Pinto-Roa fullname: Pinto-Roa, Diego P organization: Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – sequence: 5 givenname: Santiago surname: Gomez-Guerrero fullname: Gomez-Guerrero, Santiago organization: Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay – sequence: 6 givenname: Miguel orcidid: 0000-0002-6867-7080 surname: García Torres fullname: García Torres, Miguel organization: Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain
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Copyright	2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2019 by the authors. 2019
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SubjectTerms	Algorithms Darkness discrete entropy Entropy Feature extraction Image contrast Image enhancement Information theory Infrared imagery infrared images Light low contrast Morphology multiscale top-hat transform Radiation Random variables Visual perception
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Title	Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform
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