Abstract: Aiming at the problems in process of reconstruct images for super resolution reconstruction algorithm based on Maximum A Posteriori(MAP), a super resolution reconstruction based on Huber-Markov Random Field(HMRF) prior model is proposed. The HMRF model is used as image prior model, and the images are reconstructed with super resolution partly. Simulation experimental results show that, compared with tradition MAP algorithm, this method can reserve the edge details of reconstruction images better, and promote their qualities.

Key words: Maximum A Posteriori(MAP) algorithm, super resolution reconstruction, Huber-Markov Random Field(HMRF) model

摘要： 针对基于最大后验概率(MAP)的超分辨率重建算法在重建图像过程中存在的问题，提出一种基于Huber-马尔可夫随机场(HMRF)先验模型的超分辨率重建方法，采用HMRF作为图像先验模型，对图像进行分段超分辨率重建。仿真实验结果表明，与传统的MAP算法相比，该方法能更好地保存重建图像的边缘细节，有效提高重建图像的质量。

关键词: 最大后验概率算法, 超分辨率重建, Huber-马尔可夫随机场模型

CLC Number: 

• TP391.72