在集成电路的反向分析中，为了降低复杂度，通常需要将彩色图像变换成灰度图像，即将彩色图像的3个灰度分量图像融合得到一幅新的质量更高的灰度图像后再进行后续处理。由于IC(integrated circuit)线网图像具有局部相似性，因此仅在自动选取的局部孤立线邻域内进行融合以得到适用于全局的最优线性组合系数。为了描述图像中感兴趣的特征，为局部孤立线建立了一种新的线模型，并将基于模型的融合分为特征提取、特征增强和噪声抑制3步来完成。实验结果表明，基于局部线模型的融合方法在增强感兴趣的特征和提高图像质最上优于传统算法。

In reverse analysis of integrated circuits, three components of a color IC line-net image are often needed to be fused to a gray one to reduce complexity. Due to the local similarity in IC images, fusion is only performed in an automatically selected local neighborhood to get the global optimal weights in this paper. A new line model is constructed to describe the feature of interest and the model based fusion is divided into feature extraction, feature enhancement and noise suppression. Experiments show the superiority of local line model based fusion algorithm over traditional methods in enhancing the feature of interest and the quality of the fused image.