加权多尺度基本形式及应用

Weighted Multiscale Fundamental Form and Its Applications

为了使多值图像的局部变化信息适合单值图像的处理,提出了加权多尺度基本形式,其中单值图像被赋予不同的自适应权重,单值图像的变化量越大,对应的权重也就越高.将该方法分别应用于图像融合、彩色图像增强、各向异性扩散和彩色图像复原4个方面.与基于多尺度基本形式的方法及其他方法相比较,文中方法取得了更好的应用效果.

A weighted multiscale fundamental form （WMFF） is proposed to make the multiscale gradient information of multivalued image suitable for a single-valued image. Taking into account of the difference between image components, we assign different weights to different components, and the weights are adaptive and correlated to all gradients of image components. The larger the gradient magnitude, the higher the corresponding weight. WMFF has a variety of applications： image fusion, color image enhancement, anisotropic diffusion and color image restoration. Compared with multiscale fundamental form （MFF） based and other techniques, WMFF based techniques have better performance.