In order to stitch multiple photos into a larger panoramic photo, the application needs to know how to stitch adjacent photos. This requires the use of the overlapping area of ​​adjacent photos. The application identifies the key point information in the overlapping area to determine the positional relationship between two adjacent photos, and then stitches the two photos into a new photo with no gaps or ghosting. This step is repeated until all photos are stitched together, thus obtaining a complete panoramic photo with wider content.

The application uses the key point information in the overlapping area to achieve position recognition and positioning. If there is not enough key point information in the overlapping area, such as a large number of blocks of the same color and areas with insufficient changes, the application cannot extract enough key point information for position recognition and positioning. At the same time, if there are continuous image repeating areas in the overlapping area, such as repeated shapes, the application will not be able to determine how to stitch them together, because there are too many feasible stitching schemes for repeated images, and different schemes will result in completely different final output images.

When we take partial photos, the shooting position is fixed, which will ensure that the same object in all photos will have almost the same image in different photos. If the shooting position changes, the same object will have different images in different photos, such as different angles of a building. Although the building is still the same building, the images, light and shadows at different angles are different. This will lead to the failure of key point information comparison in the overlapping area, and then the failure of the final synthesis. Although our application has a built-in image difference correction function that can correct small-scale image differences, as the image difference increases, even if the final panoramic photo is synthesized, there will be gradually increasing virtual images, which will significantly affect the quality of the final film. Of course, this situation only applies to taking panoramic photos, scanning and stitching large-format flat images, such as large-format oil paintings, murals, blueprints, large-scale microscope imaging, large-scale satellite remote sensing, aerial photography, etc., which are basically not affected by changes in shooting position.

For a composite photo, there will be different automatic cropping schemes, which will eventually present different photo contents. If automatic cropping is used, users can only accept the current result, which may not meet your expectations. We provide a convenient manual cropping function, you can freely crop the stitched photos according to your own expectations.

The pixels and resolution of a single photo are limited. By stitching multiple local higher-resolution photos into a complete photo, you can get a photo with ultra-high resolution, ultra-high resolution, which can still have amazing resolution when you zoom in. This is something that a single photo cannot achieve.