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Image fusion algorithm using rough sets theory and wavelet analysis

机译:使用粗糙集理论和小波分析的图像融合算法

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Wavelets with their multiresolution property, have been proved to be effective in the integrating of the coarse features and finer resolution details of source images to produce a good fused image. The theory of rough sets has emerged as a major mathematical approach for managing uncertainty that arises from inexact, noisy, or incomplete information. Image fusion algorithm using rough sets and wavelet analysis is proposed in this paper. Multifocus images are enhanced using rough sets, then fused them using Db4 wavelet. The proposed fusion scheme is examined on images which are contaminated by salt-pepper noise. Entropy is used to evaluate image quality. Experimental results demonstrate the effectiveness of the image fusion algorithm.
机译:已经证明,具有它们的多辨别属性的小波在集成粗略特征和更精细分辨率的源图像的细节中有效,以产生良好的融合图像。粗糙集理论已成为管理不确定性的主要数学方法,这些方法是不精确,嘈杂或不完整信息。本文提出了使用粗糙集和小波分析的图像融合算法。使用粗糙集增强多焦点图像,然后使用DB4小波融合它们。所提出的融合方案在通过盐辣椒噪声污染的图像上检查。熵用于评估图像质量。实验结果证明了图像融合算法的有效性。

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