鉴于暗原色先验算法能复原不同雾浓度和场景深度的图像,而基于非局部算子概念的NL-CTV(Non-Local Color Total Variation)模型能较好地保持图像边缘和纹理等特征,融合暗原色先验与NL-CTV模型,提出了一种新型单幅彩色图像去雾模型。通过暗原色先验得到精确的大气光强度和大气传输函数,然后推导包含大气光强度和大气传输函数的非局部能量泛函,再通过引入辅助变量和Bregman迭代参数,为其设计相应的快速split Bregman算法来求解该模型。将该算法与He算法、暗原色先验和Retinex算法的实验结果进行分析比较,从而验证了该模型不论从视觉上,还是客观数据上都要优于其他两种算法。
Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.
矢量图像噪声去除的变分模型必须考虑不同通道图像间的耦合以保持图像边缘,但所得到的模型复杂、计算效率低,且不同耦合方法对应的模型的边缘保持质量不同。本文首先设计了目前已经提出的这类变分模型的快速Split Bregman算法,然后通过大量数值实验对不同模型的边缘保持特性和计算效率进行了比较。所研究的模型分别使用LTV(layered total variation)规则项、MTV(multichannel total variation)规则项、CTV(color total variation)规则项、PA(polyakov action)规则项和RPA(reduced polyakov action)规则项。实验结果表明CTV模型对矢量图像去噪边缘保持最好,其他依次是PA模型、MTV模型、RPA模型和LTV模型;LTV模型计算效率最高,其他依次是MTV模型、RPA模型、CTV模型和PA模型。