Enhancement Algorithm Based On Fuzzy Logic For Infrared Images

Image enhancement based on fuzzy theory for infrared images has been mainly researched in this paper. Three algorithms are presented bases on maximal fuzzy entropy theory in spatial domain, which are non-linear stretching method in fuzzy sets, improved enhancement methods based on plateau histogram equalization and adaptive liner stretching method with two thresholds. The results suggest that each algorithm has its advantage in some respect. Subsequently, another method in frequency domain according to wavelet theory and fuzzy sets is presented, in which the coefficients of low frequency are intensified by fuzzy logic algorithm, and the high frequency wavelet coefficients are de-noised by filtering methods. Experimental results show that the algorithm can prominently improve the contrast of low quality images, and additionally, get rid of the noises.