基于显著边缘信息的大气湍流图像盲复原

摘要

Turbulence is an important motion of atmosphere, which affects the imaging system seriously, and causes image distortion and blur. The randomly changing turbulence makes it difficult to estimate the devolution kernel and the atmospheric turbulence image restoration is ill-conditioned. we propose an atmospheric turbulence image restoration method based on priors of distinct edges. Firstly, the images are rectified. Then, we fuse the registered images and deblur the image to obtain the final image using a new method based on the distinct edge prior. In the single image deblurring schedule, we detect the distinct edges and predict the “sharp vision” of them, and use them to estimate the value of blur kernel. Finally, in order to restore the sharp images, we employ winner filter to deconvolute the images. The algorithm archives recovering much image details and sharpening edges and avoids the artifacts, which is of great practice.%大气湍流是大气的一种重要运动形式，对成像系统造成严重干扰，使图像产生畸变、模糊。文中提出一种基于显著边缘信息的大气湍流图像复原算法。首先，对每一帧图像进行畸变矫正，将矫正后的图像序列融合产生一幅图像。然后提出一种利用图像显著边缘信息估计图像退化核函数的方法，检测融合后的图像的显著边缘并重构出清晰图像的显著边缘，并以此估计图像退化核函数值。最后利用该核函数的估计值，使用维纳滤波器进行空间域的反卷积运算，恢复出清晰图像。实验结果表明本文算法能有效还原出清晰图像，锐化图像边缘，并抑制人工噪声，具有较高实用价值。