In view of low gain in contrast and definition of image obtained by th e existing image enhancement methods,an adaptive enhancement method is proposed based on non-subsampled she arlet transform(NSST) and constraint of human eye perception information fidelity.Firstly,the input imag e is decomposed by NSST into a low-frequency sub-band and several high-frequency sub-bands.Then the high- frequency sub-band coefficients are enhanced by a nonlinear transform gain function,while the low-frequency sub-b and is processed through local blocking enhancement method.Because the traditional local blocking enhancement method has the problem of discontinuity between image blocks,which results in distortion,the constraint o f human eye perception information fidelity is introduced.And then a classical linear optimization model is establ ished according to the constraint to obtain the optimal enhancement parameters,thus the enhancement of low-frequenc y sub-band is accomplished. Finally,the processed low-frequency sub-band and high-frequency sub-bands a re fused and the desired enhanced image is reconstructed.Large numbers of experimental results demonstrate that c ompared with 4congener enhancement methods put forward in recent years,the proposed method can achieve images with superior subjective visual effects and has a 50% average increment in quantitative evalua tion indicators,such as definition, local contrast and global contrast.Moreover,its real-time performance is also satisfactory.