In traditional multi-exposure image fusion methods, once the target moves, the phenomenon of “ghosting” occurs in the final fused image. Most existing de-ghosting algorithms inherit substantial data from the reference image. Once the underexposure/overexposure occurs in the reference image, the final fusion result is affected. To remedy this, herein, a multi-exposure image fusion de-ghosting algorithm based on image block decomposition is proposed. First, the reference image is divided into two areas, i.e., normal exposure and underexposed/overexposed areas, both of which are individually processed. To detect the ghost area more accurately, the proposed algorithm decomposes the multi-exposure image block into three independent parts, i.e., signal structure, signal intensity, and average intensity. Ghost detection is then performed by detecting structurally consistent image parts, following which inconsistent parts are removed, the three image parts are fused, and the required image parts are reconstructed and added to the final fused image. Experimental results of this algorithm's validation show that compared to existing de-ghosting algorithms, the proposed algorithm achieves better visual effects and improves computational efficiency.