方向对比度和区域标准差相结合的图像融合  

Image fusion based on directional contrast and region standard deviation

作　　者：林卉[1,2,3] Ruiliang Pu 梁亮[1] 张连蓬[1] 

机构地区：[1]江苏师范大学测绘学院,江苏徐州221116 [2]School of Geosciences of University of South Florida,Tampa,Florida 33620 [3]中国矿业大学环境与测绘学院,江苏徐州221009

出　　处：《计算机工程与应用》2014年第6期31-34,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(No.411101428);国家科技支撑计划(No.2012BAH31B00);江苏省自然科学基金(No.BK2012145);现代工程测量国家测绘地理信息局重点实验室经费资助项目(No.TJES1204);地理空间信息工程国家测绘局重点实验室经费资助项目(No.201310);江苏省高校自然科学研究面上项目(No.12KJB420001)

摘　　要：小波变换的图像融合方法已成为现今研究的一个热点。但几乎所有的算法都是在小波域不同尺度上分别对高频系数和低频系数进行融合,没有考虑到它们之间固有的相关性。为此,提出了一种基于方向对比度和区域标准差最大的融合新算法,主要特点是在低频部分采用加权因子自适应调节参数融合,以减少边缘模糊,对于高频部分采用方向对比度和局部区域窗口标准差最大值作为高频分量,突出对比度和局域细节,实验表明:融合后影像信息量丰富,地物轮廓清晰可辨,对比度大大加强,空间分辨率得到了提高,最大限度保留了原始影像的光谱信息,是一种可行有效的融合方法。A new multi-resolution analysis fusion algorithm introducing directional contrast and region window standard deviation is proposed, which considers the correlation between approximation and details. Weighted factors are adaptively adjusted to gain fused low frequency parts, meanwhile, directional contrast maximum and local small window standard deviation maximum are respectively adopted to form fused high frequency parts from decomposed details. Experiments show that fused image using the new algorithm considering the correlation between decomposed low frequency and high frequency coefficients is prior to that of other algorithms focusing on merging these coefficient separately regardless of visual effect or objective assessment metrics. In contrast, the fused image by the new algorithm is rich in information, features are clear, greatly enhancing contrast, improving spatial resolution and retaining spectral information of original images. Obviously, it is feasible and effective.

关 键 词：小波分解 多分辨率分析 高频系数 低频系数 方向对比度 区域标准差 

分 类 号：P237[天文地球—摄影测量与遥感]