Medical Image Enhancement Method Based on Mode Decomposition

2012 ◽  
Vol 1 (1) ◽  
pp. 21-31 ◽  
Author(s):  
Huiyan Jiang ◽  
Binbin Lou ◽  
Shiyang Liao
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Mode Decomposition ◽  
Enhancement Method ◽  
Medical Image Enhancement

Medical Image Enhancement Method Based on Wavelet Transform and Mode Decomposition

2013 ◽  
Vol 389 ◽  
pp. 930-935 ◽  
Author(s):  
Ao Shuang Dong ◽  
Bin Bin Lou ◽  
Hui Yan Jiang ◽  
Qiang Tong ◽  
Guang Ming Yang ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Image Enhancement ◽  
Empirical Mode Decomposition ◽  
Medical Image ◽  
Enhancement Effect ◽  
Mode Decomposition ◽  
Enhancement Method ◽  
Image Edge ◽  
Bidimensional Empirical Mode Decomposition ◽  
Medical Image Enhancement

Traditional medical image enhancement method has some disadvantages. They can not significantly improve the medical image edge, texture and detailed information. Besides the enhancement effect is susceptible to interference noise information. This paper proposed enhancement algorithms combining bidimensional empirical mode decomposition and the wavelet edge enhancement method. The first step is using the method of bidimensional empirical mode decomposition to process medical image, achieve image information with different frequency. And then our method using wavelet transform to enhance different frequency image edge, texture information. Through the comparison of proposed method with the existing method, it has been verified the proposed method has a better effect in the detail enhancement of medical images.

Medical Image Enhancement Using Edge Information-Based Methods

2017 ◽  
pp. 123-148
Author(s):  
S. Anand
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Hyperbolic Function ◽  
Edge Information ◽  
X Ray ◽  
Enhancement Method ◽  
Chest X Ray ◽  
Medical Image Enhancement

Medical image enhancement improves the quality and facilitates diagnosis. This chapter investigates three methods of medical image enhancement by exploiting useful edge information. Since edges have higher perceptual importance, the edge information based enhancement process is always of interest. But determination of edge information is not an easy job. The edge information is obtained from various approaches such as differential hyperbolic function, Haar filters and morphological functions. The effectively determined edge information is used for enhancement process. The retinal image enhancement method given in this chapter improves the visual quality of the vessels in the optic region. X-ray image enhancement method presented here is to increase the visibility of the bones. These algorithms are used to enhance the computer tomography, chest x-ray, retinal, and mammogram images. These images are obtained from standard datasets and experimented. The performance of these enhancement methods are quantitatively evaluated.

A New Medical Image Enhancement Method Based on Human Visual Characteristics

2014 ◽  
Vol 543-547 ◽  
pp. 2543-2546
Author(s):  
Ai Bin Dong ◽  
Yun Feng Zhang ◽  
Yi Fang Liu
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Human Visual System ◽  
Medical Image ◽  
Region Of Interest ◽  
Enhancement Method ◽  
Visual Characteristics ◽  
Medical Image Enhancement ◽  
Human Visual Characteristics

Studying of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest (ROI) is segmented; then the Un-sharp Masking (USM) is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.

Color Medical Image Enhancement Using Y-H Model and Wavelet Homomorphic Filtering

2013 ◽  
Vol 411-414 ◽  
pp. 1020-1024
Author(s):  
Hua Liang ◽  
Zhen Tao Zhou ◽  
Hao Feng ◽  
Li Jun Ding ◽  
Ju Ping Gu ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Color Image ◽  
Color Space ◽  
Inverse Transformation ◽  
Homomorphic Filtering ◽  
Enhancement Method ◽  
Rgb Color Space ◽  
Medical Image Enhancement

Color medical images are widely used in the field of medical diagnosis. Image enhancement is one of the most important pretreatment methods which can enhance the quality of images. In this paper, a novel color image enhancement method using Y-H model and wavelet homomorhpic filtering is put forward. The chromaticity numbers matrix and intensity numbers matrix of color images are get using Young-Helmholtz (YH) transform. The chromaticity numbers matrix remains unchanged. Wavelet homomorphic filtering method is used to process intensity numbers matrix . The enhanced intensity numbers matrix and formerly chromaticity numbers matrix are processed by Y-H inverse transformation and disply in RGB color space. The method put forward in the paper is successfully used in color medical image enhancement. Experimental results show that the method have characteristics of nondistortion, better visual effect.

Medical Image Enhancement Using Edge Information-Based Methods

Biometrics ◽  
2017 ◽  
pp. 1701-1726
Author(s):  
S. Anand
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Hyperbolic Function ◽  
Edge Information ◽  
X Ray ◽  
Enhancement Method ◽  
Chest X Ray ◽  
Medical Image Enhancement

Medical image enhancement improves the quality and facilitates diagnosis. This chapter investigates three methods of medical image enhancement by exploiting useful edge information. Since edges have higher perceptual importance, the edge information based enhancement process is always of interest. But determination of edge information is not an easy job. The edge information is obtained from various approaches such as differential hyperbolic function, Haar filters and morphological functions. The effectively determined edge information is used for enhancement process. The retinal image enhancement method given in this chapter improves the visual quality of the vessels in the optic region. X-ray image enhancement method presented here is to increase the visibility of the bones. These algorithms are used to enhance the computer tomography, chest x-ray, retinal, and mammogram images. These images are obtained from standard datasets and experimented. The performance of these enhancement methods are quantitatively evaluated.

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