Dynamic range compression and detail enhancement algorithm for infrared image.

For infrared imaging systems with high sampling width applying to the traditional display device or real-time processing system with 8-bit data width, this paper presents a new high dynamic range compression and detail enhancement (DRCDDE) algorithm for infrared images. First, a bilateral filter is adopted to separate the original image into two parts: the base component that contains large-scale signal variations, and the detail component that contains high-frequency information. Then, the operator model for DRC with local-contrast preservation is established, along with a new proposed nonlinear intensity transfer function (ITF) to implement adaptive DRC of the base component. For the detail component, depending on the local statistical characteristics, we set up suitable intensity level extension criteria to enhance the low-contrast details and suppress noise. Finally, the results of the two components are recombined with a weighted coefficient. Experiment results by real infrared data, and quantitative comparison with other well-established methods, show the better performance of the proposed algorithm. Furthermore, the technique could effectively project a dim target while suppressing noise, which is beneficial to image display and target detection.