Abstract: Focusing evaluation is the key to extending the depth of field in microscopy with stacked focus. To accurately and quickly obtain the pixel focusing position of the stacked focus image sequences and generate high-quality all-in-focus images, a focusing evaluation algorithm based on color vector space is proposed. This algorithm directly calculates color image gradients in the RGB vector space, fully utilizing the correlation between color channels, avoiding the information loss caused by traditional focus evaluation algorithms when converting color images into grayscale images, and has higher accuracy compared to simple stacking of color component gradients; Using the average Manhattan distance between the center pixel and neighboring pixels in RGB space as the focus evaluation weight can enhance the sensitivity of the focusing part, reduce the evaluation value of the defocused part, and make the focus evaluation curve characteristics tend to be idealized. Seven focusing evaluation algorithms in spatial domain, frequency domain, and statistics were selected for performance comparison experiments with the proposed algorithm. The results indicate that the proposed algorithm has better sensitivity, focusing resolution, and noise resistance in simulated and real microscopic images. The curve characteristics were significantly improved, and its application in microscope depth extension can further improve the quality of stacked focal large-depth imaging.