基于中值滤波和小波变换的红外图像去噪方法

针对红外图像对比度差、信噪比低、红外目标易被噪声干扰的缺点,提出一种自适应中值滤波和小波变换相结合的去噪方法.首先对图像进行小波变换,得到各频带子图像,对不同子图像采用不同的滤波模版进行自适应中值滤波,最后对图像进行小波重构,实现图像的去噪.将该方法与目前常用的去噪方法进行对比实验,结果表明,该算法简单有效,突出目标图像细节,可获得更好的图像视觉效果.

Infrared Image Denoising Based on Improved Median Filter and Wavelet Transformation

For infrared image with low contrast, low signal to noise ratio, and the interference of noise, an infrared image denoising method based on improved median filter and wavelet transformation was proposed. For this method, firstly, the wavelet transformation was used for decomposing the image, thus attaining all frequency band subimage; then, the improved median filter was adopted to denoise for subimage with different filter template; finally, the inverse wavelet transform was applied to synthesis image which can obtain the denoised image. Experiments were carried out to make comparisions of this method with the currently used methods, and the results showed that the new method can enhance infrared object effectively, and highlight the object image details.