多分辨力分析在自动聚焦算法抗噪声性能中的应用

自动聚焦是数码设备、计算机视觉中的一项关键技术。自动聚焦过程中,聚焦的准确性和抗噪声性能至关重要。以高频分量作为度量的聚集评价函数具有灵敏性高、聚焦准确的优点,适用于实时系统,但是对噪声十分敏感,受噪声污染时可能导致聚焦失败。因此,提出了一种具有噪声稳健性的高频分量自动聚焦评价函数。该函数通过小波多分辨力分析提取高频分量,利用了信号的每个子带的小波系数存在一定相关性,而噪声不存在这样的相关性的特点,设定高频子带阈值,认为低于阈值的系数是噪声的贡献,大致分离图像信号与噪声信号,从而将其滤除。经过大量的实验,证明提出的方法具有单峰性好、灵敏度高等优点,特别是在抗噪声性能方面有很大提高。

Application of Multi-Resolution Analysis in Anti-Noise Capability of Auto-Focusing Algorithm

Auto-focusing is a key technology in digital instruments and computer vision.In the focusing procedure,the focusing accuracy and anti-noise capability is crucial.Evaluation functions which based on high-frequency components have many advantages,such as sensitivity and focusing accuracy.They are suitable for the real-time system,however,they are easily corrupted by noise.Therefore,a new focusing evaluation function with good anti-noise capability has been proposed.Firstly,the proposed function abstracts high-frequency components through wavelet multi-resolution analysis(MRA).Some neighbor correlation exists in each sub-band coefficients,but noise is random,so the noise coefficients have no such correlation.The new function introduces a frequency sub-band threshold,supposing that the component value below than the threshold is noise,then filter it.In this way,noise and image signal could in general be separated.Experiments have proved that the proposed function has a sharp single apex as well as high sensitivity.Furthermore,it is significantly advanced in the anti-noise capability.