Abstract: In order to ensure the quality of digital radiography (DR) inspection images of complex structural workpieces with large thickness ratios and enrich their detail information, an image fusion algorithm based on whale optimization algorithm (WOA) and discrete wavelet transform (DWT) was proposed. Taking the aeroengine turbine blade as the research object, firstly, a low-frequency sub-band and a multi-scale high-frequency sub-band were obtained by using wavelet decomposition for different tube voltage transillumination subgraphs, secondly, the fusion rule of local mean square deviation weighted summation was applied to the low-frequency sub-band, and the high-frequency sub-band adopted the WOA optimization search for the adaptation coefficients and energy thresholds based on the maximization of the regional energy, and the adaptability function was constructed by the information entropy and clarity as a comprehensive fusion rule of evaluation index, and later the fused image was obtained by wavelet inversion. The experimental results showed that this method improved in information entropy, spatial frequency, standard deviation and average gradient compared with principal component analysis, Laplace pyramid transform and traditional wavelet fusion algorithms, and the detailed information of the obtained image was richer and of higher quality.