基于小波变换的图像多尺度数据融合

Multiscale Image Data Fusion with Wavelet Transform

现有的图像数据融合方法对目标检测并不十分满意 ,为了提高目标检测的分辨率 ,抑制每个传感器的检测噪声 ,提出一种基于小波变换的图像数据融合新方法 .在图像分解的高频域内 ,选择多源图像绝对值较大的系数作为重要小波系数 ;在低频域内 ,新的逼近系数通过对多源图像的逼近系数进行加权平均得到 ,然后利用重要小波系数和加权逼近系数进行小波反变换 ,即可得到融合之后的图像 .实验结果表明 ,基于小波变换的图像数据融合方法具有良好的效果 。

Existing methods for image data fusion are not quite satisfactory for object detection. To improve the resolution of target and suppress the detection noise of each sensor, a new method for image data fusion based on wavelet transform is presented. By decomposing the image with wavelet transform, wavelet coefficients and approximation coefficients at different scales are obtained. We took those coefficients with larger absolute value in\|between the multiresolution images as the important wavelet coefficients and computed the weighted mean value of the approximation coefficients. And the fused image can be obtained by using the inverse wavelet transform for the important wavelet coefficients and the weighted approximation coefficients. Experimental results show that the data fusion method based on wavelet transform is very effective and can be applied to wide research fields.