Research And Implementation On Mode Decomposition Based Medical Image Enhancement Method

Recently, with the rapid development of digital imaging technology and the improvement of the Medical digital image processing technology, especially the popularity of the medical image imaging apparatus. However, noise, artifacts or some of the existing image forming apparatus will lead to the problem that the medical image is not clear enough. These adverse factors on the one hand will give health-care workers in the clinical diagnostic process difficult, on the other hand, medical imaging itself is not clear enough, trouble will be caused in the further processing, such as medical image registration, feature extraction, three-dimensional modeling. Because of these deficiencies and shortcomings of the medical imaging, we need to deal with these medical images which have low contrast, texture is not clear and have blurred edges through image enhancement method to process. Improve the degree of recognition of medical imaging, so that the value is greater play. Therefore, the study of the medical image processing has become a hot research topic in the field of image processing and biomedical cross, at the same time, it also received more and more attention of the world.Aiming at existing medical image enhancement method is unable to prominent partand detailed information, especially the edge, texture, etc. Also it will be interfered by noise easily when medical image contrast is increased; this paper proposed mode decomposition based medical image enhancement which combining the histogram equalization with image details preservation and bidimensional empirical mode decomposition. First, through the histogram equalization with image details preservation to increase the overall image contrast, as far as possible to reduce the loss of image information; and then based on bidimensional empirical mode decomposition, the medical image has been decomposed into the image information with different frequency, then using wavelet transform and linear transformation to enhanced interested in organs, tissues and structures of the edge or the texture information. Through the comparison of proposed method with the traditional method, it has been verified the proposed method has a better effect in the detail enhancement of medical images.All of the above algorithms have been analyzed through experiments. They are proved to be effective and have highly feasibility.