This chapter introduces the image object generation process based on the multi-scale segmentation algorithm and conducts research on the optimal selection of parameters such as segmentation scale. Based on multi-scale segmentation, the multi-band segmentation quality index meanNSQI is constructed based on the internal homogeneity and external heterogeneity of the image object, and the optimal segmentation parameters are automatically selected in a hierarchical screening manner. Then, the geometric/quantity consistency difference between the segmented object and the reference object is used as the evaluation criterion to evaluate the optimal parameters. The reliability of the segmentation parameter optimization method in this book is verified using high-resolution remote sensing images of different resolutions as experimental data. In addition, a sensitivity analysis of the consistency difference evaluation index was conducted to explore the impact of multi-temporal image overlay on the segmentation parameter optimization results.