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Fuzzy Based Contrast Stretching for Medical Image Enhancement


Affiliations
1 Department of Computer Science, St. Xavier’s College, Tamil Nadu, India
2 Department of Computer Science, S.T. Hindu College, Tamil Nadu, India
3 Department of Information Technology, Manonmaniam Sundaranar University, Tamil Nadu, India
     

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Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.

Keywords

Contrast Stretching, Fuzzy Logic, Fuzzy statistics, Histogram Specification, Probability Density Function (PDF), Cumulative Density Function (CDF).
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  • Fuzzy Based Contrast Stretching for Medical Image Enhancement

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Authors

T. C. Raja Kumar
Department of Computer Science, St. Xavier’s College, Tamil Nadu, India
S. Arumuga Perumal
Department of Computer Science, S.T. Hindu College, Tamil Nadu, India
N. Krishnan
Department of Information Technology, Manonmaniam Sundaranar University, Tamil Nadu, India

Abstract


Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.

Keywords


Contrast Stretching, Fuzzy Logic, Fuzzy statistics, Histogram Specification, Probability Density Function (PDF), Cumulative Density Function (CDF).