scholarly journals Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Fei Zhou ◽  
ZhenHong Jia ◽  
Jie Yang ◽  
Nikola Kasabov
Keyword(s):  
Image Enhancement ◽  
Fuzzy Set ◽  
High Frequency ◽  
Medical Image ◽  
Medical Images ◽  
Low Frequency ◽  
Noise Removal ◽  
Adaptive Threshold ◽  
Image Noise ◽  
Medical Image Enhancement

Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect.

scholarly journals 3-D Block-Rooting Scheme With Application to Medical Image Enhancement

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 3880-3893
Author(s):  
Viacheslav Voronin ◽  
Aleksander Zelensky ◽  
Sos Agaian
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Medical Image Enhancement
Sign in / Sign up

Export Citation Format

Share Document