As the image enhancement algorithm of NonSubsampled Contourlet Transform(NSCT) domain has to adjust its parameters manually and can not enhance images adaptively, this paper proposes an adaptive image enhancement algorithm by combining histogram equalization with NSCT domain enhancement. The algorithm firstly performs the histogram equalization to the original low-contrast and noisy image. Then, it conducts the NSCT decomposition on the original image and the histogram equalized image to obtain the low frequency subband coefficients and a series of the high frequency directional subband coefficients. In the low frequency subband, the transform coefficient histogram of the original image is mapped to that of the equalized image. In each high frequency subband, the transform coefficient histogram of the original image is mapped to that of the equalized image after threshold denoising. Finally, the enhanced image is obtained by reconstruction of the modified NSCT coefficients. Experimental results show that the enhancement of the proposed algorithm is superior to that of classical histogram equalization method. As contrasted with Contourlet transform enhancement in two group of images, its 　evuluation function EMEE(Measurement of Enhanement by Entropy) values increase by 24.05%, 16.97%, 13.29% and 20.63% , respectively, which corresponds to that of NSCT non-adaptive enhancement(selecting optimal parameters manually) well. Moreover, this algorithm does not need manual adjusting parameters, and is characterized by good adaptability and practicability.