摘要
研究了小波域多聚焦图像融合方法中滤波器、分解层数、融合规则的选取问题,提出一种基于小波变换的简单融合规则。利用小波变换将图像分解成最低频逼近和不同尺度、不同方向的高频细节信息,最低频逼近反映图像的平均信息,细节包含图像的边缘。根据多聚焦图像中细节信息互补的特点,对多个待融合图像简单地取模值较大的小波系数,得到了很好的融合图像。详细讨论了不同的小波滤波器、分解深度、融合算子对融合结果的影响。对小波域图像融合算法与其它一些多分辨图像融合算法:如Laplace塔、比率塔、对比度塔、梯度塔等进行比较,得到了一些定性结论,对该领域的研究和实验有一定的指导意义。
The selection of wavelet filters, decomposition levels and fusion schemes is investigated for multi-focus image fusion in wavelet domain. Based on wavelet transform a simple image fusion algorithm is presented. By wavelet transform, an image can be represented by a low frequency approximation, which contain the average information of the image, and several high frequency details with different scales and directions, which contain the texture or edge feature of the image. For multi-focus images, there are some areas unclear in certain source images, which correspond to small wavelet coefficients and clear in other source images, which correspond to large coefficients, so we simply take the coefficients with greater modulus as the final coefficients to get a fusion image of good quality. We also discuss the influence of the wavelet filters used, decomposition levels and fusion schemes on the fusion results, compared wavelet based fusion with other multiresolution fusion, such as Laplacian pyramid, gradient pyramid, contrast pyramid and ratio pyramid. Some results are obtained, which are of great value for research and experiment in this field.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2004年第5期668-671,共4页
Systems Engineering and Electronics
基金
国家自然科学基金(60272058)
教育部青年教师奖基金资助课题
关键词
图像处理
多聚焦图像融合
小波变换
image processing
multi-focus image fusion
wavelet transform
