Data collected via infrared thermal imaging systems are primarily in high dynamic range. Thus, research on dynamic range compression and detail enhancement technology is crucial to achieve visualization of high dynamic infrared images. This paper addresses the challenges of gradient reversal artifacts, low contrast detail loss, and background noise over enhancement in traditional methods. In this paper, we propose a high dynamic infrared image compression and enhancement method based on side window filtering. First, side window filtering is used to decompose the original infrared image into basic and detail components. Then, an adaptive threshold platform histogram algorithm is designed based on the grayscale distribution of the basic component in order to compress the basic component. The detail component is enhanced using the adaptive gain coefficient generated via the weight distribution characteristics of the bilateral filter core. Finally, the basic and detail components are weighed and fused and quantified to an 8-bit dynamic range. According to experimental results, compared with classic compression enhancement methods, the proposed method has a superior edge preservation effect on strong edges, can effectively avoid gradient inversion artifacts and halo problems, and has richer detail information, better background noise suppression effect, and stronger adaptability to different scenes.