摘要
针对复杂背景下红外微弱点状运动目标的检测,提出一种基于小波域HMT模型的图像杂波抑制方法。对图像小波系数低频部分建立隐马尔可夫树模型,使用Bayesian准则估计图像背景小波系数,参照杂波抑制模型,得到杂波抑制后图像的信号加噪声模型,并通过计算Kendall秩相关系数和Friedman统计量验证了该方法残留噪声的高斯性和独立性。
Aiming at the detection of infrared faint blob-shaped moving target under complicated background, this paper presents an image clutter suppression method based on wavelet domain Hidden Markov Tree（HMT）. A wavelet-domain HMT model is used to accurately capture the dependencies across low frequency scales. It uses Bayesian criterion to estimate image background wavelet coefficients, refers to clutter suppression model to get clutter suppression image signal noise adding model. Gaussianity and independency of residual noise are also verified by using Kendall rank correlation coefficient and Friedman statistic.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第2期215-217,共3页
Computer Engineering
