A novel method of medical image enhancement based on wavelet decomposition

作者：Qinli, Zhang; Shuting, Shen; Xiaoyun, Su; Qi, Guo

来源：Automatic Control and Computer Sciences, 2017, 51(4): 263-269.

DOI：10.3103/S0146411617040113

• Biorthogonal wavelet
• Computational speed
• Histogram equalizations
• Image enhancement algorithm
• Low-frequency sub-images
• Mammographic images
• Nonlinear enhancement
• Real time requirement

The efficiency of image enhancement algorithms depends on the quality and processing speed of image enhancement. There are many algorithms to implement image enhancement using wavelet theory. These algorithms have one thing in common: they all capture image details by decomposing low frequency sub-images. In fact, a lot of details in high-frequency sub-images are also found. Enlightened by the above-mentioned facts, a novel medical image enhancement method based on wavelet decomposition is proposed by adding details from the high-frequency sub-images and decomposing the image specially with ant-symmetric biorthogonal wavelet instead of some traditional wavelets. It not only improves the image enhancement, but also overcomes the shortcomings of large computation with faster computational speed and satisfies the real-time requirement in edge detection. Simulation experiments of mammographic images are implemented by Matlab with several different methods, the results show that the proposed method is superior to some popular methods, such as histogram equalization and wavelet nonlinear enhancement.

• 出版日期2017
• 单位北京大学