Image Illumination Adaptive Correction Algorithm Based on a Combined Model of Bottom-Hat and Improved Gamma Transformation

To solve the problem that uneven illumination is inevitably to reduce the image quality, an adaptive illumination correction algorithm based on a combined model of bottom-hat and improved gamma transform is proposed to process and improve the image quality. In this paper, the multi-scale Gaussian function is adopted to estimate the image illumination components. Then, the two-dimensional gamma function is improved, and the coefficients of gamma transform are dynamically adjusted by using the obtained illumination components to realize the adaptive correction of the image. Finally, the corrected image is fused with the image transformed by the bottom-hat. Through a large number of experiments, it is verified that the proposed method can retain more detailed information, and the corrected picture does not produce small noise points with a better fidelity effect.