伽马校正
预处理器
人工智能
计算机科学
对比度(视觉)
计算机视觉
图像质量
对比度增强
模式识别(心理学)
图像处理
图像(数学)
磁共振成像
医学
放射科
作者
Mouna Sahnoun,Fathi Kallel,Mariem Dammak,Chokri Mhiri,Kheireddine Ben Mahfoudh,Ahmed Ben Hamida
标识
DOI:10.1109/atsip.2018.8364467
摘要
One of the most important preprocessing techniques is image Contrast Enhancement which is a technique that improve visual quality of an input image becoming more suitable for human analysis and perception. Numerous researches have been already developed for enhancement of Medical image for their important application, Traditional Gamma Correction is found to be one of the simplest technique for the contrast enhancement of medical image. This technique uses a set of varying parameter (y, c) which adjust effectively gray value intensity of the input image. Otherwise, Adaptive Gamma Correction technique have been appeared and have been proved its effectiveness by the use of adaptive (y, c) parameter which are determined adaptively from statistical information of input image. Traditional Gamma Correction (TGC) and Adaptive Gamma Correction (AGC) have been applied on three brain MRI modalities for patient with Multiple Sclerosis pathology. Qualitative and quantitative results are presented to illustrate the comparison of TGC and AGC to enhance the contrast of MRI images for better appearance of normal tissue and diseased tissue affected by MS pathology.
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