Vascular visualization is crucial for investigating vascular diseases, the development mechanism of chronic diseases, as well as the related diagnosis and treatment. Meanwhile, laser speckle imaging technology is widely used in vascular visualization and blood-flow monitoring, although the quality of vascular imaging is degraded by the presence of various noises. To improve the quality of deep vascular imaging, this study investigates the capability of vascular imaging and the feasibility of detecting the relative flow rate of blood flow of four existing spatial-domain lining-ratio methods via invivo experiments. Additionally, a quantitative assessment of the vascular-visualization capability based on the contrast noise ratio is introduced. The results show that the adaptive-window-space directional contrast method offers better imaging than the other three spatial contrast methods (spatial contrast, space directional contrast, and adaptive-window contrast methods). Based on an in vivo experiment, the adaptive-window-space directional contrast method maintains high-quality and high-resolution blood-flow mapping, thus retaining more microvascular structural and functional information. Consequently, more comprehensive blood-flow distribution maps are obtained, thereby facilitating the monitoring of blood flow in deep tissues.