Optimal Fuzzy Intensification System for Contrast Distorted Medical Images

Contrast enhancement plays a significant role in medical imaging technology for clinical diagnosis and observing the patient's health conditions. However, medical images may suffer from different degradations, such as poor visibility and low contrast, which are significant challenges for the automatic diagnosis of diseases. This article develops an ameliorated fuzzy transformation model to significantly enhance the contrast by adjusting the imbalanced intensity levels of medical images. The proposed optimal fuzzy intensification system (OFIS) utilizes the entire dynamic range by expanding the segmented intensity level of the input image. The fuzzy expansion process can enrich the diagnostic details of the processed image. The moth flame optimization is incorporated to optimize the gamma parameter to improve the clear visibility by adjusting the local contrast of the dark regions. Experiments on benchmark datasets reveal that the proposed method has superior performance in enhancing contrast and visibility of the local details of abnormalities in medical images compared with existing methods.