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With the development of infrared dual-band focal plane detector in the field of engineering application, the research on image fusion algorithm of dual-band infrared thermal imager based on engineering application becomes more and more important. Because the human eye can only distinguish dozens of gray scales, but can distinguish thousands of color scales. At the same time, gray images can only store one-dimensional data, while color images can contain three-dimensional data, which expands the amount of information by tens of thousands of times, and is easier to be applied to the processing and processing of machine vision related work in the field of detection, search, recognition and tracking. Therefore the research on color image fusion is becoming more and more important. At present, color image fusion is the main development trend of infrared dual-band image fusion. The mainstream color image fusion can be divided into four categories: color mapping, color transfer, color lookup table and neural network. The above four algorithms are difficult to take into account the color richness, environmental adaptability and human eye observation comfort. In this paper, the above problems, this paper proposes a class on medium wave infrared and long wave band color map image fusion algorithms, the algorithm is based on each source image pixel and image mean differences, the differences between the information more reasonably map to color print, the final fusion image has a better image perception and environment adaptability, and preserve more details. A typical dual-band infrared thermal imager application Scene was selected, and the subjective image comparison and objective index analysis were carried out by algorithm simulation and other mainstream color fusion algorithms, which proved that the algorithm was effective and feasible.
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