An image detail enhancement method to effectively visualize low contrast targets in high-dynamic range (HDR) infrared (IR) images is presented regardless of the dynamic range width. In general, high temperature dynamics from real-world scenes used to be encoded in a 12 or 14 bits IR image. However, the limitations of the human visual perception, from which no more than 128 shades of gray are distinguishable, and the 8-bit working range of common display devices make necessary an effective 12/14 bits HDR mapping into the 8-bit data representation. To do so, we propose to independently treat the base and detail image components that result from splitting the IR image using two dedicated guided filters. We also introduce a plausibility mask from which those regions that are prominent to present noise are accurately defined to be explicitly tackled to avoid noise amplification. The final 8-bit data representation results from the combination of the processed detail and base image components and its mapping to the 8-bit domain using an adaptive histogram-based projection approach. The limits of the histogram are accommodated through time in order to avoid global brightness fluctuations between frames. The experimental evaluation shows that the proposed noise-aware approach preserves low contrast details with an overall contrast enhancement of the image. A comparison with widely used HDR mapping approaches and runtime analysis is also provided. Furthermore, the proposed mathematical formulation enables a real-time adjustment of the global contrast and brightness, letting the operator adapt to the visualization display device without nondesirable artifacts.
This paper presents a noise removal and image detail enhancement 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 mapping without losing the perceptibility of details is needed. To do so, we introduce the use of two guided filters (GF) to generate an accurate base and detail image component. A plausibility mask is also generated from the combination of the linear coefficients that result from each GF; an indicator of the spatial detail that enables to identify those regions that are prominent to present noise in the detail image component. Finally, 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.