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Medical image illumination enhancement and sharpening by using stationary wavelet transform

机译:利用平稳小波变换增强和锐化医学图像

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Medical images captured by various devices have different illumination states based on chemicals used by patient prior to scanning. Consider a MRI image which has low contrast or is too bright, hence the experts cannot analysis that image due to poor representation of data in the image. In this paper we are proposing new medical image illumination enhancement and sharpening technique based on stationary wavelet transform which is addressing the aforementioned problem. The technique decomposes the input medical image into the four frequency subbands by using stationary wavelet transformation and enhances the illumination of the low-low subband image, and then it enhanced edges of image by adding the high frequency subbands to the image. The technique is compared with the conventional and state-of-art image illumination enhancement techniques such as histogram equalisation, local histogram equalisation, singular value equalisation, and discrete wavelet transform followed by singular value decomposition contrast enhancement techniques. The experimental results are showing the superiority of the proposed method over the conventional and the state-of-art techniques.
机译:由各种设备捕获的医学图像基于患者在扫描之前使用的化学物质而具有不同的照明状态。考虑到MRI图像对比度低或太亮,因此由于图像中数据的不良表示,专家无法分析该图像。在本文中,我们提出了一种基于平稳小波变换的医学图像照明增强和锐化新技术,以解决上述问题。该技术通过使用平稳小波变换将输入医学图像分解为四个频率子带,并增强了低-低子带图像的照度,然后通过向图像中添加高频子带来增强图像的边缘。将该技术与常规和最先进的图像照明增强技术(例如直方图均衡,局部直方图均衡,奇异值均衡和离散小波变换,然后是奇异值分解对比度增强技术)进行了比较。实验结果表明,所提出的方法优于传统技术和先进技术。

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