Image interpolation with hidden Markov model

We propose an adaptive image interpolation technique based on hidden Markov modeling (HMM) and maximum a posterior (MAP) estimation. The HMM incorporates the statistics of high resolution (HR) images into the interpolation process and the MAP estimation exploits high-order statistical dependency between pixels. Experimental results show that the HMM-based image interpolation technique can reproduce cleaner and sharper image details than its predecessors, while suppressing common interpolation artifacts such as ringing, jaggies, and blurring.