We propose a new dynamic range compression technique for infrared (IR) imaging systems that enhances details visibility and allows the control and adjustment of the image appearance by setting a number of tunable parameters. This technique adopts a bilateral filter to extract a details component and a coarse component. The two components are processed independently and then recombined to obtain the output-enhanced image that fits the display dynamic range. The contribution made is threefold. We propose a new technique for the visualization of high dynamic range (HDR) images that is specifically tailored to IR images. We show the effectiveness of the method by analyzing experimental IR images that represent typical area surveillance and object recognition applications. Last, we quantitatively assess the performance of the proposed technique, comparing the quality of the enhanced image with that obtained through two well-established visualization methods

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The visualization of IR images on traditional display devices is often complicated by their high dynamic range. Classical dynamic range compression techniques based on simple linear mapping, reduce the perceptibility of small objects and often prevent the human observer from understanding some of the important details. Thus, more sophisticated techniques are required to adapt the recorded signal to the monitor maintaining, and possibly improving, object visibility and image contrast. The problem has already been studied with regard to images acquired in the visible spectral domain, but it has been scarcely investigated in the IR domain. In this work, we address this latter subject and propose a new method for IR dynamic range compression which stems from the lesson learnt from existing techniques. First, we review the techniques proposed in the literature for contrast enhancement and dynamic range compression of images acquired in the visible domain. Then, we present the new algorithm which accounts for the specific characteristics of IR images. The performance of the proposed method are studied on experimental IR data and compared with those yielded by two well established algorithms

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