The goal of FLIR image enhancement is to obtain a good quality display by compressing the global scene dynamic range while enhancing the local area contrast. This paper presents the investigation and the implementation of six candidates for FLIR image enhancement and shows some experimental results. The six enhancement candidates are: (1) variable threshold zonal filtering, (2) statistical differencing operator, (3) unsharp masking, (4) prototype automatic target screener technique, (5) constant variance, and (6) histogram equalization. All the enhancement techniques make use of the local nonstationary mean, the local variance, or both, to achieve edge enhancement or contrast stretching in local regions. The local nonstationary mean and the local variance, in each case, are computed by a two-dimension rolling window averaging processor. Finally, an experiment based on subjective criteria to judge the enhanced image quality was conducted. The results showed that the variable threshold zonal filter, prototype automatic target screener, and unsharp masking methods were the superior techniques.