基于二维小波变换的图像除雾技术

Study on image mist-removing technology based on 2D wavelet transform

基于小波分析的图像增强在很大程度上消除了噪声,恢复了图像,同时保留了图像中的部分高频细节(奇异性部分),采用了二维小波图像增强除雾方法,理论分析和实践仿真表明:小波图像增强算法能有效地减少图像中的噪声,同时还能较好地保留图像的边缘和纹理信息。得出当图像包含较少的细节,本文方法能有效的让噪声和信号区分开来,和传统的方法相比较有很大优势,适合应用到飞行试验中的结论。

The image enhancement based on wavelet analysis largely removes the noise and restores the image, while preserving the high frequency details of the image （singularity part）. This paper introduces the wavelet enhanced theory, analysis and practice show that, wavelet image enhancement algorithm can effectively reduce the noise in the image, also can better retain the image edge and texture details. When images contain less detail, this method can effectively distinguish noise and signal, this is a great advantage in image enhancement compared with the traditional methods and is suitable for application in flight test.