Third-generation thermal cameras have high dynamic range (up to 14 bits) and collect images that are difficult to visualize because their contrast exceeds the range of traditional display devices. Thus, sophisticated techniques are required to adapt the recorded signal to the display, maintaining, and possibly improving, objects' visibility and image contrast. The problem has already been studied in relation to images acquired in the visible spectral region, while it has been scarcely investigated in the infrared. In this work, this latter subject is addressed, and a new method is presented that combines dynamic-range compression and contrast enhancement techniques to improve the visualization of infrared images. The proposed method is designed to meet typical requirements in infrared sensor applications. The performance is studied through experimental data and compared with that yielded by three well-established algorithms. Evaluation is performed through subjective analysis, assigning each algorithm a score on the basis of the average opinion of human observers. The results demonstrate the effectiveness of the proposed technique in terms of perceptibility of details, edge sharpness, robustness against the horizon effect, and presence of very warm objects.