Block-Based MAP Superresolution Using Feature-Driven Prior Model

• Main Authors: Feng Xu, Tanghuai Fan, Chenrong Huang, Xin Wang, Lizhong Xu
• Format: Article
• Language: English
• Published: Hindawi Limited 2014-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2014/508357

In the field of image superresolution reconstruction (SRR), the prior can be employed to solve the ill-posed problem. However, the prior model is selected empirically and characterizes the entire image so that the local feature of image cannot be represented accurately. This paper proposes a feature-driven prior model relying on feature of the image and introduces a block-based maximum a posteriori (MAP) framework under which the image is split into several blocks to perform SRR. Therefore, the local feature of image can be characterized more accurately, which results in a better SRR. In process of recombining superresolution blocks, we still design a border-expansion strategy to remove a byproduct, namely, cross artifacts. Experimental results show that the proposed method is effective.