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| 基于小波域维纳滤波的光纤面板暗影检测 |
| Optical fiber panel shadow detection based on wavelet domain Wiener filtering |
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| DOI： |
| 中文关键词: 小波去噪 维纳滤波 暗影检测 噪声模型 |
| 英文关键词:wavelet denoising Wiener filtering shadow detection noise model |
| 基金项目: |
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| 摘要点击次数: 4194 |
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| 中文摘要: |
| 通过分析光纤面板透光图像的噪声性质,提出在小波去噪的始末对图像取对数、指数变换,成功转换噪声模型,有效去除高斯及斑点噪声。并提出在小波域采用维纳滤波算法以增强去噪功能,实现更为有效地去除光纤面板透光图像中的噪声。最后对去噪图像进行暗影检测,实验结果表明,采用此算法进行去噪,检测出的暗影定位更加精准,冗余信息大量减少,有效提高了图像分割质量。 |
| 英文摘要: |
| By analyzing the noise properties of optical fiber panel (OFP), a method is proposed by applying logarithm and exponent in the beginning and the end of wavelet denoising algorithm. An efficient noise transformation model is obtained, and this new model can realize removing Gaussian and speckle noise effectively. To enhance the denoising performance, Wiener filtering method is used in the wavelet domain, realizes removing noise in image more effectively. At last, the shadow on the OFP is detected by using the denoised image. Experimental results show that the detected shadow can be more accuracy by using the proposed method with much redundancy information saving and higher image segmentation quality. |
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