基于细节特征融合的低照度全景图像增强 ; Low-light panoramic image enhancement based on detail-feature fusion

A low-illumination panoramic image enhancement algorithm based on a weighted fusion of detail-features is proposed, which can improve the quality of a low-illuminance panoramic image. Firstly, the illuminance component is extracted by bilateral filtering, and enhanced by adaptive gamma correction and contrast-limited adaptive histogram equalization. Then, the three illumination information is fused to get the final illumination component. In the reflection component estimation, an adaptive adjustment function is proposed to correct the reflection information. Finally, the corrected light component and the reflection component are multiplied to get the enhanced image. The experimental results show that the proposed algorithm can not only improve the image brightness and gain more detailed information, but also remove the noise, and it makes the color of an image more natural and abundant.