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Stitching Images

Image stitching lets you combine multiple image tiles to create a single high-resolution image that is beyond the normal aspect ratio and resolution of a microscope's field of view. For best results, the acquired image tiles should have overlaps with distinctive features that can be used as reference points for aligning tiles accurately.

If you are unfamiliar with image stitching, you can follow a step-by-step tutorial that explains the main features of the Dragonfly Image Stitcher (see Image Stitching Tutorial).

Image Stitching Challenges

Sometimes, aligning images based on their image content is not always easy or even possible. For example, when two overlapping regions have very little content it can be almost impossible to tell how they should be positioned. Or when the overlapping region depicts a structure like a straight line that is translationally invariant it may not be possible to automatically derive a precise position of the overlapping images. In such cases, you may need to work on sub-sections of the tiled image mosaic and then stitched the aligned sections together.

You should also note that poor image quality, such as low contrast or the presence of excessive noise, can adversely affect the performance of the automated alignment methods. For such cases, you may have to process your images accordingly before attempting any stitching operation (see Image Filtering). Pre-processing may also be required if the brightness and contrast of the unique image tiles varies within your dataset.

 

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