曲波去噪后利用独立分量峰度分析增强图像盲源分离性能

G. Attia
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引用次数: 0

摘要

本文提出利用高效的数字信号处理(DSP)方案来解决图像损坏问题。提出了一种基于小波包分解(WPD)和峰度标准的曲线去噪和盲源分离(BSS)方法。该方案旨在提高从损坏图像中去除噪声的性能。为Lena和Boat选择了两个源图像来测试模拟。源图像已被噪声源损坏。最后对研究结果和提出的方案进行了比较研究。结果的结果已经证实;在所有讨论的技术中,所提出的技术对于提高图像质量是最有效的。
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Performance Enhancement of Corrupted Images Using Independent Component Analysis by Kurtosis for Blind Source Separation After Curvelet Denoising
The current paper proposes to remedy the problem of corrupted images using efficient digital signal processing (DSP) scheme. The proposed scheme named Curvelet denoising followed by Blind Source Separation (BSS) by Wavelet Packets Decomposition (WPD) and Kurtosis standard. The proposed scheme aims to enhance the performance of removing the noise from corrupted images. Two source images for Lena and Boat have been chosen for testing the simulations. The source images have been corrupted by sources of noise. A comparison study has been performed between the performance of the last studies and the proposed scheme. The outcomes of the results have confirmed that; of all the addressed techniques, the proposed technique is the most efficient for improving the picture quality.
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