Image-enhancement is in order to improve the organizational structure of the details and meet the requirements of machinery.After the wavelet decomposition and reconstruction on the images in a multilayer method

and then the multistorey low-frequency approximation factors and the details of all levels of decomposition are dealt with

so as to achieve the objective of enhancing images.The second-generation Curvelet enhancement algorithm acts on the images for nonlinear enhancing

according to the sub-band’s noise levels

and the last step is to process anti-enhanced image transformation by the algorithm.The contrasting experiments show that the second-generation Curvelet enhancement algorithm has better effects on the overall and the local details than the wavelet enhancement algorithm

and is superior for image enhancement in suppressing the setting noise

highlighting the details of goals and improving the contrasting effectiveness.