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

• 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
• ISSN: 1099-4300; 1099-4300
• DOI: 10.3390/e21030244

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.