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| Figure 1: A single target (black rectangle) on a white background. MTF mapper can detect any number of such shapes in your input image; the target objects need not be perfectly rectangular either, as some deviation from perfect 90-degree corners is allowed. |
This approach did pay off, and still does, allowing users to design their own test charts that just work with MTF Mapper without requiring specific support for each custom test chart design.
As it turns out, many users have a very different workflow which does not allow them to specify their own chart. Examples of this include Jack Hogan's analysis of the DP Review test chart images, or Jim Kasson's razor-blade focus rail experiments. This type of workflow produces a rectangular Region Of Interest (ROI) that contains only a single edge. Figure 2 illustrates what a typical input image from this use case looks like.
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| Figure 2: A rectangular ROI containing a single slanted edge. |
In the past, MTF Mapper could only process images that look like Figure 2 by specifying the -b option, which would add a white border around the image, thereby transforming it to look more like the expected input convention illustrated in Figure 1. This was a bit of a hack, and has some severe drawbacks. The most prominent disadvantage of the -b option is that the automatic dark target detection code in MTF Mapper could fail to detect the target if the edge contrast was poor, or if the edge was extremely blurry. Fussing with the detection threshold (-t option) sometimes helped, but this just highlighted the fact that the -b option was a hack.
From MTF Mapper version 0.5.21 onwards, there is a new option, --single-roi, which is intended to replace the use of the -b option when the input images look like Figure 2.
The --single-roi input mode completely bypasses the automatic thresholding and target detection code, and instead assumes that the input image contains only a single edge. The ROI does not have to be centered perfectly on the edge, but I recommend that your ROI must include at least 30 pixels on each side of the edge. MTF Mapper will automatically restrict the analysis to the region of the image that falls within a distance of 28 pixels from the actual edge, so it does not hurt to have a few extra pixels on the sides of the edge (meaning the left and/or right side of an edge oriented as shown in Figure 2).
A typical invocation would look like this:
mtf_mapper.exe --single-roi -q image.png output_dir
which would produce two files (edge_mtf_values.txt, edge_sfr_values.txt) in output_dir. The second and third columns of edge_mtf_values.txt give you the image coordinates of the centre of the detected edge (not really that useful in combination with --single-roi), and the fourth column gives you the measured MTF50 value. To learn the mysteries of the format of the edge_sfr_values.txt file you must first signal the secret MTF Mapper handshake.
Note that it is also possible to use the --single-roi mode in conjunction with the MTF Mapper GUI, provided that your images have already been cropped to look like Figure 2. Just add the string "--single-roi" to the "Arguments" field of the Settings dialog; now you can view the SFR curve of your edge as described in this post. Update: From MTF Mapper 0.6.20 onward you can use the menu option File/Open single edge image(s) as a much more convenient method of processing cropped edges in the GUI.
You can still use the --bayer red option with the --single-roi option to process only the red channel (for example) from an un-demosaiced Bayer image, such as produced by dcraw -4 -d;
just be careful that your ROI is cropped such that the starting row/column of the Bayer pattern is RGGB (the only format currently supported by MTF Mapper).
