海水本身运动的复杂性以及海水与其它环境因素所产生的干扰物理场，往往使得海上小目标的探测尤为困难。因此，以可见光图像序列中海面小目标检测为研究对象，提出了核函数 -马尔科夫随机场 (Markov Random Fields，MRF)前景分割模型。该模型利用所提出的邻域相关核函数背景模型对图像序列的求解结果作为 MRF的观测值，建立了用于海上小目标检测的 MRF模型，进一步增强了空间相关信息，克服了多高斯模型的缺点，具有较强的海面小目标检测能力，对海浪噪声抑制效果明显。

It is very difficult to detect the small target over water in the marine environment because of the complexity of the water movement and the physical field produced by the water interacted with environment. So we mainly studied foreground segmentation for small target in visual image based on Markov Random Fields (MRF). A foreground segmentation method was proposed based on kernel function and MRF. In this method, the special and temporal correlation is used in the kernel function between neighbor pixels. We took the probability distribution of the kernel function method as the observed value of the MRF and get the energy function of the MRF. Results show that our method is applicable to low speed small target segmentation in sea image.