基于循环检测的气动退化图像混合域去噪算法

气动退化图像中存在先验信息未知以及噪声成分复杂不易进行滤波处理的问题,为此,提出一种气动退化图像混合域去噪算法。设计针对高斯噪声、泊松噪声、固定值脉冲噪声和随机值脉冲噪声的混合检测方法,使用改进的滤波方法在空域去除固定值脉冲噪声和随机值脉冲噪声,进行非下采样轮廓波变换多层分解,在变换域使用阈值方法去除高斯噪声和泊松噪声。进行噪声循环检测,设定迭代停止条件控制算法循环从而实现算法自适应。仿真实验结果表明,该算法的噪声检测性能和滤波性能较好,图像细节信息得到正确恢复。同时,算法复杂度较低,实时性较好,可满足气动退化图像去噪处理的需要。

Mixed Domain Denoising Algorithm of Turbulence Degraded Image Based on Cycle-detection

To solve the problem of difficulty in denoising owing to unknown transcendent message and complex noise components, a mixed domain denoising algorithm of turbulence degraded image is put forward. A mixed noise detection algorithm aiming at every noise components is designed. Improved denoising methods are used to wipe off settled-valued and random-valued impulse noise in spatial domain. Threshold disposals based on disassembly of Nonsubsampled Contourlet Transform（NSCT） are done to wipe off Gaussian noise in transibrm domain, and a cost function is designed to implement adaptive disaggrega-tire layers. Noise cycle-detection is done, and an iterative washed-up condition is set to achieve adaptive algorithm. Simulation experiments show that noise detection performance and denoising performance is better, and detail information of degraded image is resumed. Meanwhile, the complexity of the algorithm is low and the real-time is better. All above make sure this algorithm satisfy the need of denoising of aero-optics degraded image.