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.
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.
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.