基于噪声分析和稀疏正则化的图像盲复原方法

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.

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

In the course of maritime search and rescue, infrared image captured by helicopter airborne infrared 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 regularization 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 edges 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 quality.Compared with other methods, our method has a better effect on real blurry images.