Technology for multi-focus image fusion based on wavelet transform

Yong-qing Chen, L. Chen, Hong-jie Gu, Kun Wang
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引用次数: 6

Abstract

Since the sole focus can't capture the high-quality image of multi-association plastic gear tooth profile's flaw detail on different end surface, these flaws couldn't be detected simultaneously. When it comes to the two images focused on different gear ends, the highly detailed image is required due to the large quantity and complex profile of gear teeth. In view of the subject above, some fusion rules of multi-focus image, which adopt big high-frequency coefficient and mean value of low-frequency coefficient, are proposed in this paper based on wavelet transformation. Then suitable wavelet coefficient and decomposition layers are adopted to fuse the multi-focus image. Experimental results show that the fusion image has a high quality as well as low calculation and the tooth profile is greatly different from the background. So the proposed method shows great foreground in real time detection.
基于小波变换的多焦点图像融合技术
由于单焦点无法捕捉到不同端面上多关联塑料齿轮齿形缺陷细节的高质量图像,导致这些缺陷无法同时检测。当涉及到两个图像集中在不同的齿轮末端时,由于齿轮齿的数量大和复杂的轮廓,需要高度详细的图像。针对上述问题,本文基于小波变换,提出了采用高频系数大、低频系数均值的多聚焦图像融合规则。然后采用合适的小波系数和分解层对多聚焦图像进行融合。实验结果表明,该融合图像质量高,计算量低,且牙齿轮廓与背景有较大差异。因此,该方法在实时检测中具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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