Image enhancement algorithm of Dongba manuscripts based on wavelet analysis and grey relational theory

2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2017-10-01 DOI:10.1109/ICEMI.2017.8265812

Xiao Xinyu, Wu Guoxin, Zhuo Chunmei, Geng Qiaoman, Di Chunyan

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引用次数: 1

Abstract

Image enhancement is an important part of the image processing of Dongba manuscripts. For the low-contrast and fuzzy Dongba manuscripts image, in this paper, an image enhancement algorithm based on wavelet analysis and grey relational analysis is proposed. Firstly, the wavelet transform is used to decompose the Dongba manuscripts image into three levels, and the corresponding low-frequency components and high-frequency components are obtained. Then, the interference signal and the useful signal in the high frequency component are distinguished by the grey relation analysis theory. Finally, inverse wavelet transformation is used to reconstruct the image so that the contrast enhancement and background suppression can be achieved. The experimental results show that compared with the conventional filtering method and wavelet threshold denoising enhancement method, the proposed method has the highest peak signal-to-noise ratio, suppresses the noise while enhancing the image details and improving the image contrast.

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基于小波分析和灰色关联理论的东巴手稿图像增强算法

图像增强是东巴手稿图像处理的重要组成部分。针对低对比度、模糊的东巴手稿图像，提出了一种基于小波分析和灰色关联分析的图像增强算法。首先，利用小波变换将东巴手稿图像分解为三个层次，得到相应的低频分量和高频分量;然后，利用灰色关联分析理论对高频分量中的干扰信号和有用信号进行区分。最后，利用小波反变换对图像进行重构，实现图像的对比度增强和背景抑制。实验结果表明，与传统滤波方法和小波阈值去噪增强方法相比，所提方法具有最高的峰值信噪比，在抑制噪声的同时增强了图像细节，提高了图像对比度。

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2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)

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