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小波域隐马尔可夫树模型在图像去噪中的应用 被引量：2

Application of Wavelet-Domain HMT Models in Image Denoising
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摘要 小波域隐马尔可夫树(HMT)模型被广泛应用于统计信号和图像处理中,它成功描述了真实图像小波系数在尺度之间的相关性和依赖性,很好地体现了小波变换的延续性和非高斯性。这里通过构建图像小波域HMT模型,在应用期望最大(EM)算法估计HMT模型的参数之后,对小波系数进行贝叶斯估计达到去除噪声的目的。实验结果表明,去噪效果好于其他小波去噪算法。 Wavelet-Domain HMT models has been applied in statistic signal and image processing. The features of the wavelet coefficients between the scales of real-world image are captured, such as correlation and persist- ency and it is incarnated the Persistency and NonGaussianity properties of the wavelet coefficients. The Wavelet-Domain HMT model was built and the EM algorithm was used to estimate the parameters of the HMT model. At last Bayesian MAP was used to estimate the wavelet coefficients. The experimental results showed that the denoising method was more efficient than the other method based on wavelet transforms.
作者 吴石虎 余旭初 许敏 石磊
机构地区 信息工程大学测绘学院 [
出处 《测绘科学技术学报》 北大核心 2010年第2期120-122,共3页 Journal of Geomatics Science and Technology
关键词 小波变换 隐马尔可夫树模型 贝叶斯估计 图像滤波 四叉树 wavelet transforms HMT （Hidden Markov Tree） Bayesian estimation image denoising Quadtrees
分类号 P237.3 [天文地球—摄影测量与遥感]
  • 相关文献

参考文献8

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共引文献3

同被引文献14

  • 1侯建华,田金文,柳健.一种迭代小波域维纳滤波算法[J].华中科技大学学报（自然科学版）,2006,34(4):24-26. 被引量：8
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测绘科学技术学报
2010年 第2期

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