基于Laplacian金字塔和小波变换的医学CT图像增强算法

对医学图像进行增强可提高信息的利用率。传统的图像增强方法应用于医学图像时处理效果一般,存在诸多问题,如在增强图像的同时使图像的细节丢失,减弱了图像中目标的边缘信息,降低了图像的对比度。针对上述问题,提出一种基于小波变换和Laplacian金字塔分解的图像增强算法。首先,对原医学图像进行小波变换分解,得到处理结果；然后,对原医学图像进行Laplacian金字塔分解,得到医学图像的高频信息；最后,利用小波变换的结果和Laplacian金字塔分解的结果进行重构,得到增强后的图像。实验结果表明,该方法的增强效果明显优于传统的图像增强算法,对医学图像具有较好的增强效果,同时能更好地抵抗噪声。

Medical CT Image Enhancement Algorithm Based on Laplacian Pyramid and Wavelet Transform

The enhancement of medical images can improve the utilization of information. The traditional image enhancement method applied in medical image has many problems,such as the loss of image details,the weakening of the target edge information and the decrease of the image contrast.To solve above-mentioned problems,a new image enhancement algorithm based on wavelet transform and Laplacian Pyramid decomposition was proposed in this paper.First,the original medical image is decomposed by wavelet transform.Then,the high frequency information of medical image is decomposed by Laplacian Pyramid.Finally,the results of wavelet transform and Laplacian decomposition of Pyramid is used to reconstruct the image.Experimental results show that the proposed method is better than the traditional image enhancement algorithm,which can better enhance medical images and resist noise.