基于噪声分析和稀疏正则化的图像盲复原方法

A blind restoration method for blurry images based on noise analysis and sparsity regularization

在海事搜救过程中,机载红外相机拍摄的红外图像由于直升机振动、气流扰动、高速飞行以及红外相机摆扫等因素,严重影响图像质量.根据直升机载红外相机成像特点,提出了一种基于噪声分析和稀疏正则化的图像盲复原方法.该方法首先分析了成像过程中的噪声分布,并对噪声进行预处理,再根据稀疏表达理论,用图像边缘的稀疏先验信息指导点扩散函数复原,接着通过非盲复原方法得到目标图像,将目标图像作为下一次迭代的输入图像,如此循环迭代得到清晰图像.最后,对仿真模糊图像和实拍模糊图像进行了复原实验.实验结果表明这种方法能有效改善图像质量,并且在处理实拍运动模糊图像时,相比其他复原方法效果更好.

In the course of maritime search and rescue, infrared image captured by helicopter airborne in- frared camera has a poor image quality because of the helicopter vibration, air turbulence, high speed flight and infrared camera sweeping. According to the imaging characteristics of the helicopter airborne infrared camera, a blind restoration method for blurry images based on noise analysis and sparsity regu- larization was proposed. Firstly, noise distribution in the imaging process is analyzed and the noise is pre-processed. Then, according to the sparse representation theory, sparse prior information of the ed- ges in the images is used to guide the restoration of PSF. After that, we can obtain the target image through non-blind method. The target image will be used in the next iteration. The iteration will not end until a clear image is obtained. Experiments were performed both on simulated blurry images and real blurry images. Experimental results show that our method can effectively improve the image quali- ty. Compared with other methods, our method has a better effect on real blurry images.