Gamma correction is a necessary operation for a digital image before it is sent to display. Uneven illumination images have low resolution and a lot of information is covered. In order to better removal of light effects and reproduce truly plain circumstances, this paper presents a new local adaptive gamma correction method. The experiment shows this method makes the brightness distribution more uniform and proved that the method compared with other methods that have better correction results.
The images of outdoor scenes obtained in haze, fog and other weather phenomena are usually have poor contrast and color fidelity. In order to get a clear view of the image taken under bad weather, this paper for the image degradation in fog and haze, we detailed analyzed the image degradation causes and fuzzy mechanism and made some meaningful work for improving the existing defogging method and introduing new ideas. The experimental results demonstrate the new method abilities to remove the haze layer as well as provide a reliable depth map.
KEYWORDS: Temperature metrology, Thermography, Infrared radiation, Black bodies, Infrared imaging, Infrared detectors, Signal processing, Environmental sensing, Medical imaging, Data conversion
This paper describe a research theoretically of the conversion result to the surface temperature based on long wave infrared detector, proposed a temperature measurement, then validate it by experiments. First, it introduces the constitution and measurement principle of the medical infrared thermal imager. Then, the conversion drift characteristic of infrared detect is described, the experimental data under variable environment is analyzed, and a temperature measurement and a drift compensation formula is proposed. Finally, some experiment with black body was accomplished. The results show the temperature error is under 0.3°C, confirm the validity of the measurement.
For imaging equipments, exposure is one of the crucial factors for evaluating the quality of imaging. The correct method of exposure is the key to obtain high-quality image. Traditional calculation of exposure is slow in adaptation under extreme environment. In addition, the object of imaging under extreme light usually cannot achieve suitable gray level. To obtain accurate and effective control of automatic exposure under back light and front light environment, this article divides shoot scenes into different regions, applying the method of fuzzy logic to give each region a different weight number, and finally allowing it to correctly carry out automatic exposure. This method can manage imaging under special light conditions without being affected by the position of the main object. Experiments show that this method can effectively control automatic exposure under all kinds of environments.
Fisheye lenses have the advantages of short focal length and large field of view. However, by using the “non-similar” imaging principle, they artificially introduce a large barrel distortion. In order to improve the quality of the images correction of distortion is required. This article analyzes the polar distortion correction model, raised a simple distortion coefficient calibration method and the use of bilinear interpolation method for gray level interpolation. Compared to other methods, this method is easier to reinforce and achieves high accuracy, and it can be easily implemented in the hardware system. At the end of the paper we introduced a device correction for a fisheye CCD camera. Based on the original data, a distortion correction model is established. In order to minimize the error, the correction was divided into three sections, and the image is well recovered.
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