Research On Adaptive Weighted Histogram Enhancement Algorithm Of Infrared Image

The infrared imaging systems are used in a wide range of applications in military and civilian areas with fast development of modern infrared technology. For the effect of infrared imaging principle and environment, the infrared image has high background, low contrast ratio, narrow gray-level range and low signal noise ratio characteristics, which bring people the inconvenience to identification and detection on the image. In order to get good quality infrared images, the obtained infrared image is necessary to be enhanced. So, it is an important step to enhance infrared image in the technology of infrared image processing.In this paper, the enhancement algorithm of infrared image is studied through heightening image contrast ratio, restraining noise and enhancing image detail based on the characteristics of infrared images and conventional enhancing methods. The enhancement algorithms of infrared images are applied with the various methods to contrast the effect by simulation.On the base of analyzing the principle of image histogram, aiming at the phenomenon of gray-level merger and details losing, and integrating frequency information in spatial processing, a new method containing frequency characteristics, adaptive weighted histogram infrared image enhancement algorithm is discussed. By analyzing the grayscale information of each pixel in the original image, frequency factors are applied to original histogram to get the weighted histogram, and then the weighted histogram with a platform threshold, finally using another frequency factors to adjust each pixel of image that balanced, then the image was enhanced.Theories and simulation experiment proves that the proposed algorithms in this paper turn to be concise and self-adaptable and can be used for handling hardware real-time processing, bring about a better enhancement to the infrared image.