针对Huber-Markov随机场作为图像先验进行MAP超分辨率重建时先验约束的有效性问题,通过分析重建过程中Huber惩罚函数与图像空间灰度变化分布特性的相互关系,提出一种根据图像空间灰度变化统计特性,在超分辨率重建迭代过程中动态确定Huber函数阈值的方法。实验结果表明,该方法可根据不同图像的边缘特性,自适应确定Huber惩罚函数阈值,在有效抑制噪声的同时,保持重建图像的边缘和细节信息。

For the constraints validity problem of the Huber-Markov random field prior model in MAP super-resolution, an adaptive threshold HMRF model is proposed in this paper to make an adaptive choice of the threshold of the Huber edge penalty function. In iteration, by analyzing the relationship between the Huber penalty function and the distribution character of the image spatial gray level variation, statistical properties of the image spatial gray level variation is used as the basis for dynamically determining the threshold. Experimental results show that the proposed method can choose the threshold of Huber penalty function adaptively for images with different edge characteristics, restrain the noise, and preserve the edges details effectively.