A fast and adaptive enhancement algorithm for low illumination images based on wavelet transform is presented. RGB color image is converted to HSV color space, and the luminance component V is decomposed to low frequency sub-band and high frequency sub-bands by discrete wavelet transform (DWT). The illumination component is estimated and removed using bilateral filtering from the low frequency subband quickly, and the high frequency sub- bands corresponding to the image edges and texture are enhanced and de- noised using transform of fuzzy set. Based on the proposed histogram objective function, the contrast of the resulted V image is enhanced adaptively and quickly by employing the optimization method combining the Powell with the simulated annealing algorithm. The visibility improved color image is generated by combining the enhanced V image with H and S chrominance components. The experimental results show that the proposed algorithm can improve the visibility of low illumination images quickly and effectively.