基于双密度双树复小波变换的红外图像降噪算法

The Mage Denoising Algorithm Based on Double-density Dual-tree Complex Wavelet Transform

为提高红外图像质量,提出了基于双密度双树复小波变换的降噪算法。在相同尺度内相邻小波间频带间距更小,在变换域的频带分得更细,描述的方向信息更丰富,能够有效提取红外图像的低频和高频信息,使用双变量模型在变换域进行降噪处理,最后通过小波逆变换重构红外图像。该算法能有效滤除噪声,同时保留更多细节,获得更好的评价指标及视觉效果。

In order to improve the quality of the infrared image,this paper proposes a denoising algorithm based on double-density dual-tree complex wavelet transform.The double-density dual-tree complex wavelet has smaller frequency band spacing between adjacent wavelets in the same scale,finer frequency band division in the transform domain,and richer description direction information.It can effectively extract the low-frequency and high-frequency information of infrared image.The bivariate shrinkage model is used to denoise the wavelet coefficients.Finally,the infrared image is reconstructed by inverse wavelet transform.This algorithm retains more details while filtering out noise and obtains better evaluation indexes and visual effects.