Marco Romagnoli

Bio: Marco Romagnoli is an academic researcher from Selex ES. The author has contributed to research in topics: Image compression & High dynamic range. The author has an hindex of 2, co-authored 3 publications receiving 64 citations.

New technique for the visualization of high dynamic range infrared images

Abstract: 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.

Dynamic range compression and contrast enhancement in IR imaging systems

Abstract: 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.

Automatic Focusing Techniques for Infrared Sensors

Abstract: In this paper we study passive focusing techniques for infrared sensors. We present a survey of existing focus measures , i.e. functionals that give an estimate of the quality of focus as a function of the lens position. We synthesize the material proposed in the literature and show that all the approaches exploit the same general layout differing only for the choice of the filtering technique used to extract the image details . We present and discuss experimental results obtained on real infrared data taken in many operating conditions. The experimental analysis aims at comparing the quality of the focus measures and at evaluating their impact of the subsequent algorithm that searches the best focus position of the lens. For this purpose, we propose a comparative analysis based on three important properties of the focus measure: symmetry, smoothness and peakdness.

Display and detail enhancement for high-dynamic-range infrared images

Abstract: Dynamic range reduction and detail enhancement are two important issues for effectively displaying high-dynamic-range images acquired by thermal camera systems. They must be performed in such a way that the high dynamic range image signal output from sensors is compressed in a pleasing manner for display on lower dynamic range monitors without reducing the perceptibility of small details. In this paper, a new method of display and detail enhancement for high dynamic range infrared images is presented. This method effectively maps the raw acquired infrared image to 8-bit domain based on the same architecture of bilateral filter and dynamic range partitioning approach. It includes three main steps: First, a bilateral filter is applied to separate the input image into the base component and detail component. Second, refine the base and detail layer using an adaptive Gaussian filter to avoid unwanted artifacts. Then the base layer is projected to the display range and the detail layer is enhanced using an adaptive gain control approach. Finally, the two parts are recombined and quantized to 8-bit domain. The strength of the proposed method lies in its ability to avoid unwanted artifacts and adaptability in different scenarios. Its great performance is validated by the experimental results tested with two real infrared imagers.

New temporal high-pass filter nonuniformity correction based on bilateral filter

Abstract: A thorough analysis of low convergence speed and ghosting artifacts in temporal high-pass filter correction has been undertaken in this paper and it has found out that the keys of these problems are the interference of a large sum of unrelated scene information in the nonuniformity correction (NUC) process. In order to overcome these drawbacks, a new scene-based NUC technique based on bilateral filter has been developed. This method separates the original input frames into two parts and it estimates the NUC parameters only by using the residuals. The experimental results have shown that it can significantly increase convergence speed and reduce ghosting artifacts.

Non-uniformity correction techniques for infrared imaging devices

Abstract: Various techniques are disclosed for performing non-uniformity correction (NUC) for infrared imaging devices. Intentionally blurred image frames may be obtained and processed to correct for FPN (e.g., random spatially uncorrelated FPN in one embodiment) associated with infrared sensors of the infrared imaging device. Intentionally blurred image frames may be used to distinguish between FPN associated with the infrared sensors and desired scene information. Advantageously, such techniques may be implemented without requiring the use of a shutter to perform flat field correction for the infrared imaging device.