A new kind of infrared image adaptive contrast enhancement approach based on simulated annealing algorithm and incomplete Beta function is given. Firstly

an efficient criterion is given based on gray level histogram of input image. Input image contrast type is determined by the criterion mentioned above

and then the criterion is used to determine the searching space of gray transformation parameters and guide the search orientation and the selection of initial values of simulated annealing algorithm. The optimal gray transformation parameters are obtained in the parameter space with the simulated annealing algorithm. Thus an optimal gray transformation curve is obtained and global contrast enhancement is done to the input image based on the optimal gray transformation curve. The performance of the new approach is analyzed. Lots of experiments have been done in order to validate the efficiency of the new approach. Based on the experimental result

the new approach can enhance the global contrast of the infrared image effectively while it also keeps the details of the target in the infrared image well. In visual quality

the new approach is better than traditional histogram equalization method and un sharp mask method.