# A Scene Graph Similarity-Based Remote Sensing Image Retrieval Algorithm
## 3 Remote Sensing Image Retrieval Algorithms Based on Scene Graph Similarity
### Scene Diagram Construction  
A scene graph is a graphical data structure applied to encode and organize information in a scene, comprising object instances, object properties, and the relationships among objects. It possesses strong representation capabilities and is widely applied in the field of computer vision. In remote sensing imagery, targets are predominantly static objects, and the relationships among them are mainly spatial positioning. Relative positioning is crucial for the determination of semantic associations, and the application of directional relationships enables a more precise description of the spatial arrangements and interactions among objects in geographical scenes. This method captures the subtle differences among objects in a spatial scene, thereby enhancing the understanding of the semantic information in images.  
Considering different retrieval scenarios with distinct data characteristics, this research employed different connection methods to construct scene graphs, adapting to various retrieval requirements. These connection methods include fully connected, randomly connected, nearest neighbor connected, star connected, and ring connected methods, which are described below.  
1. Fully connected: Each node is directly connected to every other node in the graph, capturing the relationships among all nodes but introducing redundancy with the increase in node number.
2. Randomly connected: Each node is probabilistically connected to other nodes in the graph, decreasing the connection number while maintaining information transfer among nodes.
3. Nearest neighbor connected: Starting from a selected node, other nodes are incrementally added to the graph based on their proximity to the already selected nodes. This method effectively captures the local structure and similarity in the data, improving retrieval and analysis efficiency.
4. Star connected: One central node is directly connected to all other nodes, while connections among other nodes are absent. This configuration is appropriate for scenes with a clear center or theme, emphasizing information related to the central node for easier retrieval and understanding.
5. Ring connected: Nodes are connected in a circular manner where each node is connected to its adjacent nodes. This method protects the spatial information and layout relationships among targets, capturing the periodic relationships among the data.  
The process of constructing the scene graph is shown in Figure 9. The remote sensing image on the left can be used to build different scene graphs based on the various connection methods, visually demonstrating the characteristics of each method. This figure includes the object detection results of the remote sensing image, as well as the node attribute table and adjacency matrix constructed based on the object detection results. The node attribute table lists the category and positional attributes of each object, while the adjacency matrix shows the connection relationships between different objects. Based on these results, scene graphs were constructed using five different connection methods: fully connected, randomly connected, nearest neighbor connected, star connected, and ring connected.  
In Figure 9, each node represents an object, including the object's category and positional attributes, denoted as (L, x, y, w, h), where L represents the category, and (x, y, w, h) represents the position. Each edge represents the spatial relationship between two objects, expressed as (d, \(\theta\)), where d is the distance between the starting node and the target node, and \(\theta\) is the angle from the starting node to the target node in a polar coordinate system constructed with the top-left corner of the remote sensing image as the origin.