Infrared thermal image, with many noises, blurred details and large ranges, needs to be processed on human observation applications. As the dynamic range of the infrared detector data is usually much larger than that of the display device format, infrared image needs to be gray-scale compression before displaying to human eyes. In order to achieve a good vision-observation effect and to retain the major information at the same time, it is proposed an algorithm of non-continuous gray-scale histogram enhancement, based on the human visual characteristics.
Firstly, through researching on gray-scale characteristics curve of the human visual on the image resolution, it configures a “visual resolution histogram” (VRH), which has non-continuous gray scales determined by the gray-scale characteristics curve.
Secondly, it integrates both equalization method and order-mapping themes, to transform infrared thermal image into the format of continuous and even distribution on gray scales in visual resolution histogram. As well as, it proposes a “Central Segment Histogram Enhancement” (CSHE) to keep mean brightness effects on the visual system.
Finally, experiments show that the proposed algorithm provides rich layers and good resolutions of displaying image on human view, as well as reduces the adverse phenomenon of scale moderation in conventional histogram equalization theme.
Faced with complex background on aerial moving platform, infrared point target detection apply background suppression policy to greatly improve detection efficiency. However, due to the background relative motion, it presents challenges for target detection. From remote observation in the air, background movement could be approximately regarded as plane rigid motion, which is the sum of translation and rotation movement. Until now, existing algorithms by comparing the adjacent frames of infrared image have good performance in the detection of translation motion, but poor effect in the situation of the rotational motion. It is proposed a rigid motion estimation algorithm based on infrared background feature point set (IRMBE) .Firstly, by processing statistical movement characteristics of the feature point set on infrared background image, the algorithm gauges out the translation motion vector. Secondly, it uses Monte Carlo method in background feature point set to estimate the vector of rotation axis and the angular velocity. Experiments show that the algorithms can perform good estimation of the complex background rigid movement, in the application of space-based Infrared observation.