A segmentation-based adaptive image enhancement method inspired by the self-adjust features of HVS

作者：Yin, Hui^*; Lyu, Guohao; Luo, Xiaoyue; Li, Chenglong

来源：International Journal of Machine Learning and Cybernetics, 2017, 8(6): 1895-1905.

DOI：10.1007/s13042-016-0567-2

• Image enhancement
• Illuminance estimation
• Segmentation based approach
• Color recovery
• Gaussian curvature

This paper focuses on the enhancement of the images captured in insufficient or non-uniform lighting conditions. Inspired by the self-adjust features of HVS (Human Vision System), a Segmentation-Based Adaptive Image Enhancement (SAIE) method is proposed to improve the visibility of degraded images. First the local characteristics of different parts of each image (called sub-block images) obtained by image segmentation are described by Gaussian curvature, then the parameters of Gaussian filter for each sub-block image are chosen adaptively according to its local characteristics to estimate the illumination component of the whole image accurately. After that, adaptive dynamic range adjustment for the estimated illumination based on global characteristics and contrast enhancement for sub-block images are implemented. Finally, the enhancement result is obtained after color adjustment. The experiments on five typical image sets show that SAIE can provide effective and robust enhancement results. Comparative qualitative and quantitative evaluations with MSRCR, IRME and MSRCR+AL are also provided to demonstrate the efficiency and superiority of the proposed method.

• 出版日期2017-12
• 单位北京交通大学