中文说明： 马尔可夫随机场 （MRF） 模型准确是对模型图像特征的有力工具，已成功地应用于大量的图像处理应用程序。本文研究了融合的遥感图像，例如，多光谱图像融合，基于马尔可夫随机场模型的问题，并通过马尔可夫随机场模型的语境制约因素纳入融合模型。下最大的融合算法验 标准的制定，以寻求解决办法。我们的算法是适用于这两种多尺度分解 （MD）-图像融合和非 MD 基于图像融合的基础。实验结果我们的算法提供证明的融合性能改进。
English Description：
Markov random field (MRF) models are powerful tools to model image characteristics accurately and have been successfully applied to a large number of image processing applications. This paper investigates the problem of fusion of remote sensing images, e.g., multispectral image fusion, based on MRF models and incorporates the contextual constraints via MRF models into the fusion model. Fusion algorithms under the maximum a posteriori criterion are developed to search for solutions. Our algorithm is applicable to both multiscale decomposition (MD)- based image fusion and non-MD-based image fusion. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithms.