【摘要】 采用基于对比度视觉模型的图像融合最优分块搜索算法,对同一场景两幅严格配准的多聚焦图像的清晰恢复进行了深入研究.针对该算法在图像较大时融合的计算量大,耗时长,难以进行快速、实时融合等缺点,通过分析该算法固有的时间复杂性和并行性,提出了一种基于多宇宙并行量子遗传算法和对比度视觉模型的多传感器图像融合方法.实验表明,该方法融合计算速度快,并行性能理想.更多还原

【Abstract】 Multi-focus image fusion is to combine information from multiple images of the same scene for producing a merged image. A reconstructed scheme based on contrast vision model is studied briefly exploiting segmentation techniques and blocks search. The method’s computing complexity is exponentially increased with the growth of image size. After analyzing the efficiency of image fusion algorithm, the inherent complexity and the parallelism, a multi-sensor image fusion method based on multi-universe parallel quantum genetic algorithm is proposed. The experimental result shows that the efficiency of parallel computing is obviously improved.更多还原