Image De-Noising Algorithm based on Filtering and Histogram Equalization

Q3 Medicine Koomesh Pub Date : 2018-08-01 DOI:10.1109/I-SMAC.2018.8653714
Anupama Shetter, S. N. Prajwalasimha, Swapna Havalgi
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引用次数: 6

Abstract

In this paper, a collective median filtering and histogram equalization based de-noising technique is proposed for images. Initial noise detection is performed by considering neighboring pixel values then median filtering is performed to remove high density noise. The filtered image is then subjected for histogram equalization to regain correlation between adjacent pixels. The final image enhancement is done by contrast adjustment method. The experimental results show that the proposed algorithm provides high quality restored images compared to existing ones.
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基于滤波和直方图均衡化的图像去噪算法
本文提出了一种基于集体中值滤波和直方图均衡化的图像去噪技术。通过考虑相邻像素值进行初始噪声检测,然后进行中值滤波去除高密度噪声。然后对过滤后的图像进行直方图均衡化,以恢复相邻像素之间的相关性。最后用对比度调整法对图像进行增强。实验结果表明,与现有的恢复图像相比,该算法提供了高质量的恢复图像。
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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来源期刊
Koomesh
Koomesh Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
0
审稿时长
24 weeks
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