| 摘要: |
| 利用自然图像信号的分段统计稳态性可以有效地对图像信号进行建模.其分段统计稳态区域往往具有非规则的形态.采用规则窗口对图像统计稳态区域内的统计量进行估计存在较大的误差.提出一种基于概率描述的隐式分段自回归模型来刻画分段统计稳态区域形态,并基于该模型提出了一种改进的图像插值算法.实验结果表明,该方法可以较好地改善插值图像中在边缘处的模糊、振铃和噪声等瑕疵现象. |
| 关键词: 图像插值 自回归模型 分段统计稳态 加权最小二乘法 |
| DOI：10.3724/SP.J.1001.2012.04049 |
| 分类号: |
| 基金项目:国家自然科学基金(61071082); 国家发改委高技术产业发展项目(发改办高技[2010]3044 号); 北京市自然科学基金(4102025) |
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| Image Interpolation Algorithm Based on Implicit Piecewise Autoregressive Model |
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REN Jie, LIU Jia-Ying, BAI Wei, GUO Zong-Ming
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Institute of Computer Science and Technology, Peking University, Beijing 100871, China
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| Abstract: |
| The piecewise statistical stationary property of natural image signals provides an effective way to model the image signals. However, the statistical stationary region always has an irregular profile. Large mismatch errors rise when a regular shape window is adopted to estimate the statistics in these regions. This paper proposes an implicit piecewise autoregressive model based on a probabilistic description of the statistical stationary region. According to this model, an improved image interpolation algorithm is presented. The experimental results show that the proposed interpolation method can greatly alleviate the blurring, ringing, and noisy artifacts around edges in interpolated image. |
| Key words: image interpolation autoregressive model piecewise statistical stationary weighted least squares |
