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Extending depth-of-field of a digital camera using particle swarm optimization based image fusion

机译:使用基于粒子群优化的图像融合扩展数码相机的景深

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Images obtained by an optical camera are seriously affected from the limited depth of the field issue. That is, the objects located in-front-of or behind the focus of the camera are blurred. Everywhere-in-focus images can be obtained by combining focused regions of images which were captured by different focal settings. In this paper, an optimal region based spatial domain image fusion approach based on selecting sharper regions from the multi-focus source images is proposed. Size of the block type regions are optimized by using particle swarm optimization (PSO) algorithm. Quantitative and subjective experimental results of different image sets show that proposed method is better than traditional wavelet and Laplacian pyramid based and also genetic algorithm (GA) based methods.
机译:光学摄像机获得的图像会受到景深有限的严重影响。即,位于相机焦点前面或后面的对象是模糊的。可以通过组合由不同焦点设置捕获的图像的聚焦区域来获得无处不在的图像。本文提出了一种基于最优区域的空间域图像融合方法,该方法基于从多焦点源图像中选择较锐利的区域。块类型区域的大小通过使用粒子群优化(PSO)算法进行优化。不同图像集的定量和主观实验结果表明,所提出的方法优于传统的基于小波和拉普拉斯金字塔的方法以及基于遗传算法的方法。

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