Displays the dataset containing the imagery used for generating ground control points. This field is not editable.

Select the ground control point distribution mode. Two options are provided: Conventional and Uniform. The default is Conventional.

• Conventional: Divides each overlapping area into N*M sub-regions, then selects n image blocks of 512*512 size from each sub-region for tie point matching to ensure stable and reliable tie points. The generated ground control points will cover the entire overlapping area as much as possible.
• Uniform: The generated ground control points will be evenly distributed across the overlapping area. The number of points is fewer than that in the regular distribution, but the distribution is more uniform, making it suitable for images with significant internal distortion.

Available when Conventional is selected in Point Distribution Mode.

Divides each overlapping area into N*M sub-regions and sets the intensity for generating ground control points: Sparse corresponds to 3*3 sub-regions; Medium corresponds to 4*4 sub-regions; Dense corresponds to 6*6 sub-regions. The default is Medium. Higher density requires longer computation and processing time.

Available when Conventional is selected in Point Distribution Mode.

Five matching methods are provided: MOTIF, AFHORP, RIFT, SIFT, and DEEPFT. The default is MOTIF. Among these, AFHORP and RIFT support multi-modal data matching, while DEEPFT requires configuring an AI model and installing CUDA.

• MOTIF: A template matching algorithm for multi-modal imagery, characterized by using lightweight feature descriptors. MOTIF can overcome nonlinear radiation distortions caused by differences between SAR and optical images.
• AFHORP: A feature matching algorithm for multi-modal imagery. AFHORP is highly resistant to radiation distortion and contrast differences in multi-modal imagery and performs excellently in addressing issues like directional reversal and abrupt phase extreme changes.
• RIFT: A feature matching algorithm robust to large-scale nonlinear radiation distortions. RIFT not only enhances the stability of feature detection but also overcomes the limitations of using gradient information for feature description.
• SIFT: A method for extracting unique invariant features from images, used for reliable matching of objects or scenes under different viewpoints.
• DEEPFT: An image matching method based on deep learning.

Available when Conventional is selected in Point Distribution Mode.

The maximum number of points retained per image block during image matching. The range is [25,2048], and the default is 256.

Available when Uniform is selected in Point Distribution Mode.

Sets the number of seed points for tie point matching on each image. The range is [64,6400], and the default is 512. When the image texture is poor, it is recommended to increase the number of ground control points to ensure sufficient matching points and improve subsequent imagery quality.

Available when Uniform is selected in Point Distribution Mode.

Sets the method for searching seed points. The default is Raster Center Point.

• Corner Points: Uses points with distinct features within the selected region as seed points.
• Raster Center Point: Uses the center point of the raster as the seed point. This search method is random.

Available when Uniform is selected in Point Distribution Mode.

Sets the interval size between seed points. The range is [1,256], and the default is 40, with the unit being px. A larger template size results in more reliable search points but requires more time.

Available when Uniform is selected in Point Distribution Mode.

Sets the search radius for seed points during image matching. The range is [0,256], and the default is 40, with the unit being px. A larger search radius increases the matching range but also requires more time.

Available after selecting Semantic Culling of Non-Ground Points.

Selected by default. This means ground control points within cloud areas will be automatically removed based on the set dataset. If not selected, ground control points in cloud areas will be retained.

Displayed after selecting Cloud Area and is not editable.

For workflows related to DOM production, use the cloud amount data in Set Image Path.

For workflows related to DSM production, use the cloud amount data in Set Image Path (DSM/DEM).