基于显著区域和MVSC的图像拼接算法

Jinpeng Wang, Yewei Li
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引用次数: 11

摘要

将视觉注意模型与均值无缝克隆(Mean Value Seamless Cloning, MVSC)算法相结合,提出了一种基于显著区和均值无缝克隆的图像拼接算法。该算法利用视觉注意模型提取显著区域,并利用区域配准技术实现图像匹配,且MVSC算法具有良好的图像融合特性,因此对图像拼接进行了研究。对传统的视觉注意进行改进,利用改进的视觉注意模型算法获得图像重复的显著区域。图像配准算法对图像重复的显著区域进行匹配,确定源和目标的克隆域。最后,利用MVSC算法融合源图像和目标图像的克隆域,实现图像拼接。实验结果表明,本文算法不仅能自动准确地获取显著区域,而且降低了图像配准的复杂度,提高了图像拼接的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Mosaicing Algorithm Based on Salient Region and MVSC
The visual attention model and the Mean Value Seamless Cloning (MVSC) algorithm are combined to propose an image mosaicing algorithm based on salient region and MVSC. The new algorithm uses the visual attention model to extract the salient region, and to use the regional registration technology to achieve the image matching, and MVSC algorithm possess good image fusion character, so the image mosaics were studied. The traditional visual attention is improved, and using the improved visual attention model algorithm to obtain salient region of image repeated. The salient regions of image repeated are matched by the image registration algorithm to determine clone domain of the source and target. Finally, the clone domains of the source and target are fused by the MVSC algorithm, to achieve image mosaicing. Experimental results show that this paper algorithm not only can automatically and accurately obtain salient regions, but also reduce the complexity of the image registration, improve the quality of image mosaicing.
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