Image clarity evaluation functions for camera autofocus under various lighting conditions

The multispectral imaging system captures images using multiple different light sources. As the camera focuses on different light sources, the wavelength of the light changes, causing a shift in the focal length of the camera and a corresponding change in the information captured by the image. To address this issue, this paper analyzes other evaluation functions and modifies the Tenengrad function to extract image gradient information from multiple directions. The paper then proposes the SIFTQuad_Tenen image clarity evaluation function, which is combined with the SIFT feature point extraction algorithm. Experiments were conducted using three different light sources: red, green, and blue. The resulting clarity evaluation curves and related indicators were compared with those of other evaluation functions. The results show that the proposed evaluation function has good performance in all three lighting scenarios, as well as better stability and higher sensitivity than other evaluation functions.