Wolfram Language

Image and Signal Processing

Feature-Based Image Inpainting

Inpainting of large missing regions of an image may not yield realistic results if relying only on available regions of the same image. Using a representative dataset of aligned images, you can use multiple images to train an inpainting function using FeatureExtraction.

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Click for copyable input
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BaseStyle->"ImageGraphics", ImageSizeRaw->{300, 200}, PlotRange->{{0, 300}, {0, 200}}]\)}; missingparts = {\!\(\* GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJzt2LFqFFEUgOG9Vpa+gr0PYGtpG/EBEozBJkIiiG/oYxlJ4zrZ9T/VbuT7 YAYGprj83BnOzOurrxefX+x2u/uXD6eLy+/v7u4uf3x49XDx8fb+y83t9af3 t9+ub67v3l79vu3nw/Fm7QAAAAAAAOA/tR6dehnPwdKqWlpVS6tqaVUtraql VSZVJlUmVSdVp1UmVSdVJlWnVSZVp1UmVadVJlWnVSZVp1UmVadVJ1WnVSZV p1UnVadVp1WnVSdVp1WnVeZ11WnVadVp1WnVadVJ1WmVeQQ7rTqtOq06rTqt Oq06rbolVqZVt8TKtBoQq9NqQKxOq4H1p1Mv5sytjVOv6IxtY+l1yJOt9HrS wVZ6bR2Npde+f8XSa59YQ2LNiDUj1oxYM2LNiDUg1oBYA2INiDUg1oBYAwat AWPpgCG++7uVWEdsYql12DaWWodpNaDVhFYTYk1oNaHVgFadjdVpNaBVp1Wn VafVgFaZfdVplZmvMh/PmR8NmR9YnVaZVJlUmVTZ0qqSKpMqk6qTqpOqk6qz r7q1deolna0nWil2wMFWem0cbaXWHq06rYa0mtNqSKshrQAAAAAAAAAAAAAA AACAZ+cX/EUTvQ== "], {{0, 200}, {300, 0}}, {0, 1}, ColorFunction->GrayLevel], BoxForm`ImageTag["Bit", ColorSpace -> Automatic, Interleaving -> None], Selectable->False], DefaultBaseStyle->"ImageGraphics", ImageSizeRaw->{300, 200}, PlotRange->{{0, 300}, {0, 200}}]\), None, \!\(\* GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJzt2zFqm0EUhdFfqVx6C+6zALcu0yp4ATaRTRoZpIDxDrOsSIWFYmTrXjf+ Yc6BGRiY4vH17+r+afnwbZqm7cXuWt4932w2dy8/L3eP2/X29+N69evH+s/q cbW5vt9/+7s73xcTAAAAAAAAwHws/vfV48zX4pSvHmqWTpZS64R3S6n11oep xDp2JpVYB2dLqfUqSiXWXphKrEmrQpxKrCLV6LGqVIPH0ipWpho6llaxOtXA sbTKaRX7RKphY2mV0yqnVU6rnFY5rXJa5bTKaZXTKqdVTqucVjmtClLltMpp VZAqp1VBqpxWBakKUhWkymlVkKogVUOpglQFqRpKNZSqCAUAAAAAAAAAAAAA AADADFh3C1mjTFnPTb1bSq23Pkwl1rEzqcQ6OFtKrVdRKrH2wlRiTVoV4lRi FalGj1WlGjyWVrEy1dCxtIrVqQaOpVVOq9gnUg0bS6ucVjmtclrltMppldMq p1VOq5xWOa1yWuW0ymlVkCqnVU6rglQ5rQpS5bQqSFWQqiBVTquCVAWpGkoV pCpI1VCqoVRFKAAAAAAAAGCu/gHdth8q "], {{0, 200}, {300, 0}}, {0, 1}, ColorFunction->GrayLevel], BoxForm`ImageTag["Bit", ColorSpace -> Automatic, Interleaving -> None], Selectable->False], DefaultBaseStyle->"ImageGraphics", ImageSizeRaw->{300, 200}, PlotRange->{{0, 300}, {0, 200}}]\), None, None};

Covariations of pixel values in a dataset of images allow you to derive statistical features that may be used to predict missing regions.

show complete Wolfram Language input
In[2]:=
Click for copyable input
prepareTrueAndMissingData[dataset_, missingmasks_] := Module[{i, mask}, Table[ If[BinaryImageQ[missingmasks[[i]]], mask = missingmasks[[i]]; Flatten@ImageData@dataset[[i]]* Flatten@ImageData@ColorNegate@mask + Flatten@ImageData[mask]*Missing[] /. _Plus :> Missing[], Flatten@ImageData@dataset[[i]], ], {i, Length@dataset}] ];
In[3]:=
Click for copyable input
inpaintFromList[dataset_, masks_, n_] := Module[ {data, fe}, data = prepareTrueAndMissingData[dataset, masks]; fe = FeatureExtraction[data, "MissingImputed"]; Image[ArrayReshape[fe[data[[n]]], Reverse@ImageDimensions@dataset[[1]]]] ];

Feature-based inpainting is applied separately to each color channel of the third image.

In[4]:=
Click for copyable input
result = ColorCombine[ Table[ Image[inpaintFromList[channels, missingparts, 3], "Byte"], {channels, Transpose[ColorSeparate /@ images]}]]
Out[4]=

Highlight the inpainted area.

In[5]:=
Click for copyable input
HighlightImage[result, {FaceForm[], EdgeForm[{Dashed, AbsoluteThickness[1], White}], missingparts[[3]]}, ImageSize -> Medium]
Out[5]=

Compare the above with the result of Inpaint, which just uses the input image.

In[6]:=
Click for copyable input
HighlightImage[ Inpaint[images[[3]], missingparts[[3]]], {FaceForm[], EdgeForm[{Dashed, AbsoluteThickness[1], White}], missingparts[[3]]}, ImageSize -> Medium]
Out[6]=

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