A novel compressing method of high dynamic range image based on fast integrated surround Retinex model is proposed in this paper. The proposed method has two novelties. First, multiscale surround images are integrated to a single surround field, which is applied to center/surround single-scale Retinex (SSR) model. The method reduces the "banding artifact" seen in normal SSR and simplifies the complicated computational steps in conventional multiscale Retinex. Second, the Gaussian pyramid method is introduced to cut the computation time for generating a large-scale surround by tracing a "reduction" and "expansion" sequences using down and up sampling followed by linear interpolation. The computational expense is dramatically saved less than 1/100 for getting a surround by Gaussian convolution with large kernel size. The proposed model worked well in compressing the dynamic range and improving the visibility in heavy shadow areas of natural color images while preserving pleasing contrast.