基于小波包分层净化的模糊图像细节增强算法

Details Enhancement Algorithm of Fuzzy Image Based on Wavelet Packet Layered Purification

在复杂电磁环境下,动态飞行摄像机对地面采集的场景图像具有较大的模糊性,需要进行图像增强处理,提高对图像的辨识能力。传统的图像增强算法采用基准特征提取和小波轮廓掩膜处理方法,对图像的细节部分的增强效果不好。提出一种基于小波包分层净化的模糊图像细节增强算法。首先进行了图像的采集系统设计和干扰模型构建,对采集的数字图像进行小波包分层净化处理,把原始图像的细节特征作为母小波函数,计算母小波函数的时间尺度因子,以此作为数据输出,结合人工鱼群算法实现对净化处理后的图像的细节增强。仿真结果表明,该算法能有效实现模糊图像的细节增强,改善图像成像质量,两组仿真图像的峰值信噪比提高了12.4%和15.3%。

Under the complex electromagnetic environment, the dynamic flight camera on the ground to collect images of the scene is very vague, needs to carry on the image enhancement processing, improve the identification ability of image. The traditional image enhancement algorithm using datum feature extraction and wavelet contour mask processing method and details of the image enhancement effect is not good. Put forward a kind of image fuzzy enhancement algorithm based on wavelet packet layered purification details. First image acquisition system design and interference model construction, the acquisition of digital image by wavelet packet layer purification treatment, the details in the original image as the mother wavelet function, computing the time scale factor of the mother wavelet function, in order to acts as the data output, artifi-cial fish swarm algorithm realization of purification treatment of image detail enhancement. Simulation results show that the algorithm can the effective realization of the fuzzy image detail enhancement and improve the image quality of the image, two sets of simulation image peak signal to noise ratio is increased by 12.4%and 15.3%.