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Images produced by IR cameras are a specific source of information. The perception and interpretation of such image greatly depends on thermal properties of observed object and surrounding scenery. In practice, the optimal settings of the camera as well as automatic temperature range control do not guarantee the displayed images is optimal from observer's point of view. The solution to this could be the methods and algorithms of digital image processing implemented in the camera. Such solution should provide intelligent, dynamic contrast control applied not only across entire image but also selectively to specific areas in order to maintain optimal visualization of observed scenery. The paper discusses problems dealing with improvement of the visibility of low-contrast objects and presents method of image enhancement. The algorithm is based on adaptive histogram equalization. The image enhancement algorithm was tested on real IR images. The algorithm significantly improves the image quality and the effectiveness of object detection for the majority of thermal images. Due to its adaptive nature it should be effective for any given thermal image. The application of such algorithm is promising alternative to more expensive opto-electronic components like improved optics and detectors.

This paper presents the detection and identification of gases using an infrared imaging Fourier-transform spectrometer. The principle of operation of the spectrometer and the method for gases detection and identification has been shown in the paper. The variation of a signal reaching the IFTS caused by the presence of a gas has been calculated and compared with the reference signal obtained without the presence of a gas in IFTS's field of view. Some results of the detection of various types of gases have been presented too.

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