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A procedure for haze detection and removal from high-resolution satellite images using wavelet analysis (HAWAT) has been developed. It involves the analysis of the low spatial frequency information content of a scene. The image contaminated by haze is decomposed into different spatial layers with wavelet transforms. Although haze is distributed in the lower frequency layer, this layer may also contain a component of land cover that is spatially and temporally relatively stable. A haze-free reference image of the same area is used to characterize land cover. The component of the characterized land cover is then subtracted with wavelet analysis. The residual wavelet coefficients are used to construct a spatially varying mask for subsequent haze detection and removal. After smoothing, the mask is subtracted from the contaminated image to obtain a corrected image with haze-off characteristics. Both visual inspection and statistical accuracy assessment show that the haze calibration is valid and robust.
Du et al. (Tue,) studied this question.