Aiming at the current lack of multi-scale detail information in the original image based on wavelet transform image fusion enhancement algorithm,an improved image enhancement algorithm combining multi-scale wavelet transform and depth residual selection is proposed.After the original image is decomposed and extracted by wavelet transform to obtain its multi-level decomposition coefficients,different rules are used to reconstruct different levels of wavelet coefficients.At the same time,the idea of deep residual algorithm is introduced to make residuals for subband coefficients.For the high frequency subband coefficients,the proposed algorithm will calculate the coefficients of the subband residuals and the coefficients of the gradient feature fusion method,and select the maximum value of the two for fusion enhancement,while for the low frequency subband coefficients,the algorithm uses the method of averaging the gradient feature fusion enhancement coefficient and the subband residual coefficient for fusion.The algorithm is verified through experiments on MATLAB platform,compared with the comparison method,the peak signal-to-noise ratio has been improved,and the root mean square error has also been reduced,and the structural similarity has been improved.The experimental results show that the method can enhance the multi-scale detail information of the image,improve the signal-to-noise ratio of the image,and has a better image enhancement effect.