Monday 30 June 2014

Inpainting: a users’ guide

Over the past few posts I have introduced the idea of inpainting and the mathematics behind the ability to “intelligently” fill in a region based on the information provided by the rest of the image. The theory was developed by Dr Thomas Maerz, from which he constructed a set of matlab codes that simulated his ideas. Dr Martin Robinson has since developed Thomas’ ideas into a FREE GIMP plugin.

This week I present a guide to using Martin’s plugin.
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In its most basic form Martin’s code is extremely easy to use: you select a region; set a few parameters and tell GIMP to run the code. As before, we will use the plugin to remove bee from the following photo. Also, we once again use the GIMP’s extensive suite of selection tools to highlight the region we are interested in.
When you have selected the region you are interested in fire up the inpainting plugin. If it has been installed correctly (see Martin’s documentation for more information) then by default it should be in the “Filters” drop down menu under “Misc”. Once it is opened you should see a box that looks like Figure 1.

First approximation
Figure 1. The general user interface of the inpainting plugin.
In this basic case the text box should automatically be filled in with the correct details. Namely, the image shown at the top should be the area that you selected, the source should be the image you want to inpaint and the mask type should be a selection.

You will then notice that there are four parameters: epsilon, kappa, sigma and rho. These are very important and control various aspects of the inpainting algorithm. Specifically, not only do they influence what colour a chosen pixel will be, but they also influence how details will propagate into the domain. This means if there are straight lines leading into the boundary the parameters will alter how those straight lines are continued. The following box gives more detail on each of the parameters.

epsilon defines the region over which the colour is averaged. If epsilon is large then colours over a larger region are used. If epsilon is small the code only uses local colour detail to paint the new pixel.

kappa controls how the level set lines (discussed in a previous post) effect the direction of features that we want to propagate into the region. If we want the picture features to follow the level set line direction we make kappa large, otherwise we make it small.

sigma controls how much the input data is smoothed. If sigma is small then small scale features will propagate into the domain, alternatively, if sigma is large then only clear, distinct line features will be taken into the inpainting region.

rho controls the averaging of the directional information. This is needed because some of the features may be heavily directional and we may want to propagate these directions into the image. A large rho causes a large amount of information of the boundary to be averaged, leading to more accurate directional information. If there is little directional information in the boundary we make rho small.

In the basic case shown below I set the parameters to epsilon=20, kappa=100, sigma=0.01, rho=20. The way I found these numbers was partly through playing around with the sliders and partly thinking about their definitions. Since the picture is high definition we want the maths to take in detail from a large region, so we make epsilon big. Because there are a number of thin creases in the petals that we want to propagate and carry on the line we set kappa and rho high (to keep the direction) and sigma low (to keep the detail).

As you will see below even this simple approach does a good job. However, by putting in a little extra effort we can make the result so much better.
Advanced inpainting
As you may notice from the image, most of the lines meet up one the bee is removed. However, because the bee covers regions connecting the petals to the central anthers of the plant, some of the central plant detail gets propagated into the inpainted region. To stop details being propagated in to regions we do not want them we use a “stop path”.

We select the path tool from the gimp work box and draw a curve. This curve will represent the points to which the details will propagate. Since the anthers are propagating too far we draw a red line that maps closely to the anther region as seen below. As before, the black and white line represents the region selected to be inpainted.
Once we have the path defined we then go back to the plugin and select “Selection With Stop Path” in the “Mask Type” drop down menu. Once this is selected the “Stop Path” drop down menu should become selectable. In this menu we select the curve that we have drawn and, finally, click apply.

Below we show the base case (left) along with the final image of this advanced version (right), and both of these can be compared with the original (above). Hopefully, you can see that, by just applying a little more work we get a much better result.

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Over the last few posts I have introduced the idea of inpainting, met the minds behind it and, hopefully, you’ve had ago yourself. Once again, here are all the links that have mentioned over the last few weeks:

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