DocumentCode :
154729
Title :
Exponential image enhancement in daytime fog conditions
Author :
Negru, Mihai ; Nedevschi, Sergiu ; Peter, Radu Ioan
Author_Institution :
Comput. Sci. Dept., Image Process. & Pattern Recognition Group, Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear :
2014
fDate :
8-11 Oct. 2014
Firstpage :
1675
Lastpage :
1681
Abstract :
The images captured in fog conditions have degraded contrast, that makes current image processing applications sensitive and error prone. We propose in this paper an efficient single image enhancement algorithm suitable for daytime fog conditions and based on an original mathematical model, for computing the atmospheric veil, that takes into account the variation in fog density to the distance. This model is inspired by the functions that appear in partition of unity in the differential geometry field. When observing images captured in fog conditions, usually the fog has a very low density in front of the camera and this density has a non-linear increase with the distance, such that objects are no longer visible at greater distances. By using our mathematical model we are able to obtain superior reconstructions of the original fog-free image, when comparing to traditional methods. Another advantage of our method is the ability to adapt the model in accordance to the density of the fog. A quantitative and qualitative evaluation is performed on both synthetic and real camera images. This evaluation proves that our mathematical model is more suitable for image enhancement in both homogeneous and heterogeneous fog conditions. Our algorithm is able to perform image enhancement in real time for both color and gray scale images.
Keywords :
image colour analysis; image enhancement; image reconstruction; atmospheric veil; color image; daytime fog condition; differential geometry field; exponential image enhancement; fog density; fog-free image reconstruction; gray scale image; heterogeneous fog condition; homogeneous fog condition; image enhancement algorithm; image processing applications; qualitative evaluation; quantitative evaluation; Atmospheric modeling; Cameras; Equations; Image color analysis; Image enhancement; Image restoration; Mathematical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
Conference_Location :
Qingdao
Type :
conf
DOI :
10.1109/ITSC.2014.6957934
Filename :
6957934
Link To Document :
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