Authors:
Patricia Suárez
1
and
Angel Sappa
1
;
2
Affiliations:
1
Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Electricidad y Computación, CIDIS, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador
;
2
Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain
Keyword(s):
Thermal Super-Resolution, HSV Color Space, Luminance-Driven Bicubic Image.
Abstract:
This paper presents a novel approach for thermal super-resolution based on a fusion prior, low-resolution thermal image and H brightness channel of the corresponding visible spectrum image. The method combines
bicubic interpolation of the ×8 scale target image with the brightness component. To enhance the guidance
process, the original RGB image is converted to HSV, and the brightness channel is extracted. Bicubic interpolation is then applied to the low-resolution thermal image, resulting in a Bicubic-Brightness channel blend.
This luminance-bicubic fusion is used as an input image to help the training process. With this fused image, the
cyclic adversarial generative network obtains high-resolution thermal image results. Experimental evaluations
show that the proposed approach significantly improves spatial resolution and pixel intensity levels compared
to other state-of-the-art techniques, making it a promising method to obtain high-resolution thermal.