Point Spread Function Estimation for a Turbulence-Degenerated Image Based on Àtrous Wavelet Transform

The observed object images are seriously blurred because of the influence of atmospheric turbulence. The restoration is required for the reconstruction of turbulence degraded images. Point spread function (PSF) estimation, an essential part of image restoration, has no accurate estimation algorithm at present. Based on the àtrous wavelet, we deduce a novel PSF estimation algorithm. First, the àtrous wavelet at varying scales is transformed. Then, on the basis of the relation among the local maxima of the modulus of the wavelet coefficients at different scales, the Lipschitz exponent of the wavelet coefficients is computed, thus the variance of a PSF is estimated. From this estimated variance, one is able to obtain the PSF. Consequently, the object image can be restored. Experimental results show that the proposed method is highly effective with good performance.