Image segmentation using snake model with nosie adaptive fuzzy switching median filter and MSRM method

Sajal Pahariya, S. Tiwari
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引用次数: 1

Abstract

In this paper, we are using maximum similarity region merging(MSRM), anisotropic diffusion (AD), noise adaptive fuzzy switching median filter, active countour /snake model. In the proposed approach, work on both gray or color images. With the use of MSRM, merge the maximum similarity area/region. AD is used to smooth the image. NAFSM is used for removing noise from an image. In the last step, we used a Snake model for removing blur effect from an image. The results on peak signal noise ratio (PSNR), Mean square error (MSE), accuracy and time method give better performance in terms of brightness and contrast of the enhanced image remove noise and increase brightness.
基于自适应模糊切换中值滤波和MSRM方法的蛇形模型图像分割
在本文中,我们使用了最大相似区域合并(MSRM)、各向异性扩散(AD)、噪声自适应模糊切换中值滤波器、有源国家/蛇模型。在提出的方法中,既可以处理灰度图像,也可以处理彩色图像。使用MSRM合并最大相似区域/区域。AD用于平滑图像。NAFSM用于去除图像中的噪声。在最后一步中,我们使用Snake模型从图像中去除模糊效果。结果表明,在峰值信噪比(PSNR)、均方误差(MSE)、精度和时间方面,增强后的图像在亮度和对比度方面都有较好的表现。
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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