基于小波分解的湍流退化图像的快速复原算法

FAST RESTORATION ALGORITHM FOR TURBULENCE-DEGRADED IMAGES BASED ON WAVELET DECOMPOSITION

提出了一种基于小波分解的湍流退化图像的复原新方法 .该方法以 2帧同一目标的湍流退化图像作为输入 ,采用小波变换技术对两帧湍流退化图像进行多尺度分解 .利用两个低频子频段图像的傅立叶频谱估计出两湍流点扩展函数在大尺度下的离散值 ,在图像的低频子频段进行去模糊 ,而在高频子频段则主要进行抑制噪声和保边缘特征 .实验结果表明该方法十分有效 ,不但可以极大地减少计算复杂性 ,加快恢复速度 ,而且还可以很好地提高图像的恢复质量和抗噪能力 .

A new method based on wavelet decomposition is presented for the restoration of turbulence-degraded images. For this method, two turbulence-degraded images are used as the inputs, for which the multi-scale decompositions are made using wavelet transform. The discrete values of the two turbulence PSFs in large scales can be estimated by mean of the Fourier frequency spectrum of the images in low frequency subbands. Removing blur is performed in the low frequency subbands of the images while reducing noise and preserving edges are made in the high frequency subbands. The experimental results show that the proposed method is highly effective for it not only greatly reduces the computational complexity and speeds up the restoration but also enhances the quality of restoration and the ability of resisting-noise well.