Abstract:

A detail-enhanced multi-exposure image fusion method was proposed to address the problem of low weights obtained in the light and dark regions in the sequence image, resulting in the loss of details in the bright and dark regions of the fused image. Wavelet decomposition was conducted on the sequence image and the fused image based on the weight map. This process involved extracting the low-frequency components from the fused image and the high-frequency components from the edge regions, and they were fused with the high-frequency components from the non-edge regions of the sequence image. Finally, the detail-enhanced fused image was obtained through wavelet inverse transform. Experimentally, nine sets of classical multi-exposure image sequences were selected for comparison with nine multi-exposure image fusion algorithms in terms of subjective comparison and objective evaluation, respectively. The results demonstrated that the proposed method, which combined the spatial and frequency domain image fusion methods, could effectively solve the problem of detail loss in the bright and dark areas of fused images, while avoiding the problem of ringing phenomenon often encountered in frequency domain image fusion methods. The fused images were realistic, natural, and exhibited vibrant colors. The mean image information entropy value and the mean image gradient value of the fused images obtained through the proposed method were 7.655 5 and 7.027 3, respectively, ranking first and second among the ten multi-exposure image fusion algorithms. Considering both subjective and objective evaluation results, the proposed method outperformed the nine comparative methods.

Key words: multi-exposure images, image fusion, detail enhancement, wavelet transform, high dynamic range