论文标题
视觉传感器网络的多聚焦图像融合
Multi-focus Image Fusion for Visual Sensor Networks
论文作者
论文摘要
视觉传感器网络（VSN）中的图像融合旨在将来自同一场景的多个图像的信息组合在一起，以便将单个图像转换为更多信息。基于离散余弦变换（DCT）的图像融合方法在基于DCT的图像和视频标准中省时不那么复杂，因此更适合VSN应用程序。在本文中，提出了用于融合DCT域中多聚焦图像的有效算法。源图像的相应块的修改laplacian（SML）的总和用作对比标准，而SML值较大的块被吸收到输出图像中。几个图像的实验结果表明，相对于其他基于DCT的技术，融合图像的主观和客观质量都改善了所提出的算法。
Image fusion in visual sensor networks (VSNs) aims to combine information from multiple images of the same scene in order to transform a single image with more information. Image fusion methods based on discrete cosine transform (DCT) are less complex and time-saving in DCT based standards of image and video which makes them more suitable for VSN applications. In this paper, an efficient algorithm for the fusion of multi-focus images in the DCT domain is proposed. The Sum of modified laplacian (SML) of corresponding blocks of source images is used as a contrast criterion and blocks with the larger value of SML are absorbed to output images. The experimental results on several images show the improvement of the proposed algorithm in terms of both subjective and objective quality of fused image relative to other DCT based techniques.
