多小波变换在夜视图像融合算法中的应用

从微光图像和红外图像的特点出发,提出了一种基于多小波变换的夜视图像融合算法.该方法先对夜视图像进行多小波变换得到各子带的多小波系数,其低频系数采用自适应加权融合算子进行融合,高频系数先进行阈值去噪和子带增强,再采用基于频带方向的融合算子进行融合,经多小波逆变换后得到融合图像.实验结果表明,本文算法与单小波融合算法、传统融合算法相比,得到的图像能更好地突出图像的边缘特征,增强图像的可视性和清晰度,并在信息熵、峰值信噪比等客观性能指标上取得了显著的改善.

The Application of Multi-wavelet Transform in Night-vision Image Fusion Algorithm

According to the features of the infrared and micro-light images,a new algorithm of night-vision image fusion is proposed based on multi-wavelet transform.Firstly,two night-vision images are transformed by multi-wavelet to obtain the sub-band multi-wavelet coefficients.Then,their low-frequency coefficients are fused by using adaptive weighted fusion operator.Their high-frequency,coefficients conduct threshold denoising and sub-band enhanced,and then are fused by using frequency band direction fusion operator.Finally,the fusion image is obtained by multi-wavelet inverse transform.The experiments indicate that the performance of new algorithm is better than those of single-wavelet fusion algorithm and PCA fusion algorithm.It not only highlights the features of the edge of the image,but also significantly enhances the visibility and clarity of the image.And it has made significant improvements in objective evaluation criteria such as information entropy,PSNR etc.