The Research On Infrared Image Processing Based On Biorthogonal Wavelet Transform

Infrared technology is widely used as a new tool for human to discovery the mystery of nature in the field of biology, medicine, and science and military. Because of the natural environment and the inherent performance of devices, infrared image is easily contaminated by noisy, and the clarity of the infrared is much less than the clarity of the visible image, so how to remove from the noise and enhanced clarity of infrared image is the main direction of the infrared image research today. Using the infrared image analysis, it’s a better way to get hybrid informations of visible and infrared images, image fusion and provide an effective method.This paper mainly studies the infrared image de-noising, matching and fusion base on biorthogonal wavelet transform. Aiming at the shortcomings of the compromise threshold algorithm proposed an improved function, combining with the Spatially Selective Noise Filtration de-noising alorgrithm proposed on adaptive threshold de-noising algorithm based on biorthogonal wavelet and correlation. According to the features of infrared image and visible light image and image matching technology based on characteristics proposed the normalized correlation matching algorithm based on canny edge. Aiming at the shortcomings of the Intensity, Hue, saturation matching algorithm proposed the improved IHS fusion algorithm based on biorthogonal wavelet transform and object extraction, and aiming at the high-frequency components and low-frequency components of the wavelet transform proposed the appropriate improve rules of fusion. Contrasting with other algorithms through experiments, the results show that image processing algorithms proposed in this paper has better effect.