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# 2.11 Mosaicing

See figure 2.13.

These functions are useful for joining many small images together to make one large image. They can cope with unstable contrast, and arbitary sub-image layout, but will not do any geometric correction. The mosaicing functions can be grouped into layers:

The lowest level functions are `im_correl()`. and `im_affine()`. `im_correl()` searches a large image for a small sub-image, returning the position of the best sub-image match. `im_affine()` performs a general affine transform on an image: that is, any transform in which parallel lines remain parallel.

Next, `im_lrmerge()` and `im_tbmerge()` blend two images together left-right or up-down.

Next up are `im_lrmosaic()` and `im_tbmosaic()`. These use the two low-level merge operations to join two images given just an approximate overlap as a start point. Optional extra parameters let you do 'balancing' too: if your images have come from a source where there is no precise control over the exposure (for example, images from a tube camera, or a set of images scanned from photographic sources), `im_lrmosaic()` and `im_tbmosaic()` will adjust the contrast of the left image to match the right, the right to the left, or both to some middle value.

The functions `im_lrmosaic1()` and `im_tbmosaic1()` are first-order analogues of the basic mosaic functions: they take two tie-points and use them to rotate and scale the right-hand or bottom image before starting to join.

Finally, `im_global_balance()` can be used to re-balance a mosaic which has been assembled with these functions. It will generally do a better job than the low-level balancer built into `im_lrmosaic()` and `im_tbmosaic()`. See the man page. `im_remosaic()` uses the same techniques, but will reassemble the image from a different set of source images.

Figure 2.13: Mosaic functions

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