基于小波域的红外图像序列噪声分析与去噪

由于相同的去噪方法对不同噪声类型的去噪效果不一样,采用基于小波域的图像噪声类型识别方法,利用小波高频子带系数的直方图识别了图像的两类主要噪声：高斯噪声和椒盐噪声.对红外图像系列的噪声进行了分析,长波红外图像主要受到高斯噪声干扰,中波红外图像主要受到椒盐噪声干扰.提出了一种改进的小波全局阈值去噪方法.仿真实验表明,该方法较传统方法的PSNR提高了2~3 dB,处理速度较快.

Analysis and De-noising Infrared Image Series Based on Wavelet Domain

The effectiveness of one de-noising method for different noise images is different,a method based on wavelet domain for identifying image noise types was used.The histogram of wavelet HH sub-band＇s coefficients was used to identify two types of main noise： Gaussian white noise and salt pepper noise.After analyzing the infrared image series,it is found that the long-wave infrared images are mainly affected by the Gaussian white noise,the medium-wave infrared images are mainly affected by the salt pepper noise.An improved wavelet global threshold de-noising method is reported.The simulation experiments indicate that the PSNR of this method is increased by 2～3 dB,processing speed is more faster,compared with traditional methods.