Enhancement of Infrared Image Combined with Histogram Equalization and Fuzzy Set Theory

Infrared images collected by optical measure equipment are low contrast and with fuzzy image edge. In order to solve these problems, a novel method combined with platform histogram equalization and fuzzy theory is proposed. Firstly, it uses logarithm membership function to translate gray image into the fuzzy domain, then image’s edges are carried out non-linear transformations in the fuzzy domain to enhance image’s edges information. Next, the method combined with improving and adaptive platform histogram equalization is presented to improve the image contrast effectively. Finally, the fusion of two images multiplied by weighting coefficients is applied. Experimental results show that this algorithm has an excellent enhancement effect, which overcomes some shortcomings that traditional algorithms showed, such as the phenomenon of the excessive enhancement and weakening of the local gray information. Meanwhile there are more abundant details and more pleasing visual content in the enhanced images, which enables to satisfy the demands of shooting range and is of great and wide value for engineering application.