A computationally efficient IR-GCV (integer recurrent generalized cross validation) algorithm is proposed.The integer grey-scale pixels are transformed into integer wavelet coefficient,and its distribution is calculated,followed by the incorporative numeration of coefficient of the same value.Furthermore the integer recurrent procedure based on integer wavelet coefficient is applied,which take full advantage of the relevance between GCV functions under adjacent thresholds.The comparison among GCV and IR-GCV is carried out on multiple remote sensing images.When the noise standard deviation varies from 10 to 30,the time complexity of IR-GCV is only 2 percent to 0.5 percent of that of GCV,while the de-noising results still remain unchanged.The PSNR of de-noising image is 0.66 db to 6.03 db higher than that of noisy image.Besides,the time complexity of GCV increases rapidly as the noise standard deviation and scale of remote sensing image increase,while the time complexity of IR-GCV is relatively more stable.