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Image enhancement method based on fuzzy set and subdivision

机译:基于模糊集和细分的图像增强方法

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摘要

Alga microscopic image usually has a lot of noises and blurs. So a proper image enhancement algorithm which can remove noise and retain detail information is very important for alga microscopic image disposal. In the paper a new image enhancement method based on fuzzy set and subdivision is proposed. It is effective for alga microscopic image disposal. Subdivision scheme's good similarity among different subdivision layers makes the multi-resolution analysis has better approximation between the decomposed signals and the initial image. Subdivision method has strong ability to suppress noise through decomposing the initial image into low pass part. The image can be reconstructed through subdividing the low pass part of the initial image. Then the fuzzy set method is used for enhancement the reconstructed image. A special function is used as membership function in the process of fuzzification. The experimental results demonstrate the effectiveness of the proposed method for alga microscope image diaposal.
机译:藻类显微图像通常会产生大量噪点和模糊。因此,适当的图像增强算法可以去除噪声并保留细节信息,对于藻类显微图像处理非常重要。提出了一种基于模糊集和细分的图像增强新方法。对于藻类显微图像处理有效。细分方案在不同细分层之间的良好相似性使得多分辨率分析在分解信号与初始图像之间具有更好的近似度。细分方法通过将初始图像分解为低通部分来抑制噪声。可以通过细分初始图像的低通部分来重建图像。然后将模糊集方法用于增强重建图像。在模糊化过程中,将特殊功能用作隶属函数。实验结果证明了所提出的方法对藻类显微镜图像二尖瓣的有效性。

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