Analysis of quality of removing cloud for monochromatic remote sensing images

In order to show the best information of monochromatic remote sensing images,it was processed with the algorithms of wavelet transform,advanced mufti-scale Retinex,and homomorphic filter respectively.The criterions of brightness,contrast degree,production of brightness multiplying with contrast degree,information entropy,fidelity were applied to evaluate the quality for the images enhanced by 7 methods and original images.The results showed 3 points.Firstly,the values of brightness,contrast,and production of brightness multiplying with contrast were largest and their image quality was best when the images handled by mufti-scale Retinex and stretched the range of k=1 time standard deviation near the mean brightness.Secondly,the values of contrast and information entropy were biggest and their image quality was well when the images handled by wavelet transform with a high-pass filter.Finally,the value of fidelity was largest in all algorithms and their image quality was common when the images handled by homomorphic filter with n=1.The algorithms of advanced mufti-scale Retinex and wavelet transform were best for removing black cloud and white cloud in remote sensing images respectively.