%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2017/08.22.01.24
%2 sid.inpe.br/sibgrapi/2017/08.22.01.24.18
%@doi 10.1109/SIBGRAPI.2017.43
%T Top-Hat transform for enhancement of aerial thermal images
%D 2017
%A Román, Julio César Mello,
%A Legal-Ayala, Horacio,
%A Noguera, José Luis Vázquez,
%@affiliation Universidad Nacional de Asunción - Facultad Politécnica
%@affiliation Universidad Nacional de Asunción - Facultad Politécnica
%@affiliation Universidad Nacional de Asunción - Facultad Politécnica
%E Torchelsen, Rafael Piccin,
%E Nascimento, Erickson Rangel do,
%E Panozzo, Daniele,
%E Liu, Zicheng,
%E Farias, Mylène,
%E Viera, Thales,
%E Sacht, Leonardo,
%E Ferreira, Nivan,
%E Comba, João Luiz Dihl,
%E Hirata, Nina,
%E Schiavon Porto, Marcelo,
%E Vital, Creto,
%E Pagot, Christian Azambuja,
%E Petronetto, Fabiano,
%E Clua, Esteban,
%E Cardeal, Flávio,
%B Conference on Graphics, Patterns and Images, 30 (SIBGRAPI)
%C Niterói, RJ, Brazil
%8 17-20 Oct. 2017
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K thermal image, contrast enhancement, top-hat transform, mathematical morphology.
%X A thermal image is obtained by a camera that is sensitive to the thermal variation of the environment. This sensitivity in most cases affects the quality of the image obtained. Therefore, it is very important to improve the quality of thermal images in terms of contrast and details. There are different contrast enhancement techniques which introduce minor distortions, preserving the proper brightness as well as the details of the image. This work presents a top-hat transform for the improvement of grayscale aerial thermal images. The proposed method is based in the use of increasing structuring elements of similar geometry within the fundamental operations of mathematical morphology. The evaluation of the performance of the current proposed method was made with several metrics for images in grayscale. The experimental results show that the proposed method improves several thermal images which were tested, enhancing the contrast, preserving the richness of the details as well as the mean brightness and introducing less distortion in the images. The results show better aerial thermal images with less distortion and adequate brightness, which is very useful for further processes over the images.
%@language en
%3 47.pdf