Displays the dataset containing the images used for generating tie points. This field is not editable.

Based on existing adjustment file information, make newly generated tie points closer to the accuracy of existing tie points. Use the Add and Delete buttons in the toolbar to conveniently manage multiple adjustment reference files.

The adjustment file is obtained from the Block Adjustment function.

The error threshold for outlier removal in image matching. The value range is [0,40], default is 5, and the unit is px.

During image matching, the least squares method is used to fit the result points, removing points that exceed the error threshold. A larger threshold retains more tie points but increases the probability of retaining incorrect points.

Select the tie point distribution mode. Two options are provided: Conventional and Uniform. 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 corresponding point matching, ensuring stable and reliable tie points. The generated tie points will cover the entire overlapping area as much as possible.
• Uniform: The generated tie points will be evenly distributed across the overlapping area. The number of points is fewer than in regular distribution, but the distribution is more uniform, suitable for images with significant internal distortion.

Available when Conventional is selected in Point Distribution Mode.

Sets the intensity for generating ground control points: Sparse is 3*3 sub-regions; Medium is 4*4 sub-regions; Dense is 6*6 sub-regions. 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. Among them, AFHORP and RIFT support multi-modal data matching, while DEEPFT requires configuring an AI model and installing CUDA.

• MOTIF (default): A template matching algorithm for multi-modal images, characterized by using lightweight feature descriptors. MOTIF can overcome nonlinear radiation distortion caused by differences between SAR and optical images.
• AFHORP: A feature matching algorithm for multi-modal images. AFHORP has strong resistance to radiation distortion and contrast differences in multi-modal images and performs excellently in solving direction reversal and phase extremum mutation issues.
• RIFT: A feature matching algorithm robust to large-scale nonlinear radiation distortion. RIFT not only improves 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 between objects or scenes from 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 within each image block during image matching. The value range is [25,2048], default is 256.

Available when Uniform is selected in Point Distribution Mode.

Sets the number of seed points for corresponding point matching on each image. The value range is [64,6400], default is 512. When image texture is poor, it is recommended to increase the number of tie points to ensure enough points are matched, improving subsequent imagery quality.

Available when Uniform is selected in Point Distribution Mode.

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

• Corner Point: Selects points with distinct features within the 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 value range is [1,256], default is 40, and the unit is px. A larger template makes the searched points more reliable but takes longer.

Available when Uniform is selected in Point Distribution Mode.

Sets the search radius for seed points in image matching. The value range is [0,256], default is 40, and the unit is px. A larger search radius increases the matching range but also takes longer.

Displayed after selecting Cloud Area, not editable.

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

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

Available after selecting Semantic Culling of Non-Ground Points.

Selected by default, meaning building areas will be automatically identified, and tie points in those areas will be removed. If not selected, tie points in building areas are retained.