Real-time Visualization of High-Dynamic-Range Infrared Images based on Human Perception Characteristics - Noise Removal, Image Detail Enhancement and Time Consistency

This paper presents an image detail enhancement and noise removal method that accounts for the limitations on human’s perception to effectively visualize high-dynamic-range (HDR) infrared (IR) images. In order to represent real world scenes, IR images use to be represented by a HDR that generally exceeds the working range of common display devices (8 bits). Therefore, an effective HDR compression without loosing the perceptibility of details is needed. We herein propose a practical approach to effectively map raw IR images to 8 bit data representation. To do so, we propose an image processing pipeline based on two main steps. First, the raw IR image is split into base and detail image components using the guided filter (GF). The base image corresponds to the resulting edge-preserving smoothed image. The detail image results from the difference between the raw and base images, which is further masked using the linear coefficients of the GF, an indicator of the spatial detail. Then, we filter the working range of the HDR along time to avoid global brightness fluctuations in the final 8 bit data representation, which results from combining both detail and base image components using a local adaptive gamma correction (LAGC). The last has been designed according to the human vision characteristics. The experimental evaluation shows that the proposed approach significantly enhances image details in addition to improving the contrast of the entire image. Finally, the high performance of the proposed approach makes it suitable for real word applications.