rock art petroglyph and pictograph educational articles
Using Decorrelation Stretch to Enhance Rock Art Images
Presented at the Society for California Archaeology, April 23, 2005.
I have implemented this technique in the DStretch plugin to ImageJ . The plugin has options intended to be useful in rock art research.
DStretch can be a useful tool for archaeologists. The enhancement
techniques can bring out very faint pictographs almost invisible to the
eye, Figures 1-2. Subtle differences in hue are enhanced which can give clues to
superposition. Pictographs can be enhanced for publication or
presentation to viewers not capable (or inclined) to puzzle out faint
elements. I have had better results on pictograph images than
petroglyphs. Use of DStretch can be as simple as just hitting a button,
but it also contains features that will be appreciated by more
|Figure 1. Photograph of a difficult to see pictograph||Figure 2. Same photograph enhanced with DStretch|
If an area selection is made within the image the input to the decorrelation will be restricted to the colors inside the area. The enhancement will be applied to the entire image. This allows the exclusion of parts of the image that may have little to do with the area of interest, say a green bush at the side of a pictograph panel. Different decorrelation results are possible by selecting different parts of the image.
Mapping back is optional. This can create more colorful enhancements, but the colors will have little resemblance to the original. When not mapped back the colors in the image are decorrelated. If decorrelation is tried again unpredictable results occur that can switch colors and sometimes create better contrasts.
Different colorspaces give different results, especially when not mapped back, so I have implemented the algorithm in RGB, YCbCr, YUV and XYZ colorspaces. Artifacts from JPEG compression can be a problem; using YCbCr colorspace lessens the artifacts, Figures 3-6.
|Figure 3. Bighorn sheep photograph||Figure 4. Enhanced with algorithm RGB||Figure 5. Enhanced with algorithm YCbCr|
The enhanced image is false color, i.e. the colors in it can be radically different from the original, especially if not mapped back. DStretch has the ability to shift the hues in the enhanced image to increase contrast.
Each image enhances differently, depending on its own unique distribution of colors. For consistency it is possible to save an enhancement matrix that was calculated on one image and apply it to others. I have saved one matrix that I have found useful for each colorspace. Choosing custom in the matrix chooser can access these matrices. A dialogue pops up and allows for user modification of the default matrices.
Another useful enhancement technique, not related to decorrelation stretch, is the manipulation of the hue and saturation of the image. DStretch can do hue histogram equalization and saturation stretching.
DStretch also contains a tool that allows a region of the enhanced image to be isolated by hue and then added back to the original image. This can be used to isolate an enhanced element and display it in the original image.
DStretch Help http://www.dstretch.com/DStretchHelp.html
 Gillespie, et al. 1986: Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches. Rem. Sens. Environ., 20, 209-235.
 Gonzalez and Wintz, 1977: "Digital Image Processing", Addison-Wesley, Reading, MA.
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© 2005 All rights
reserved. This article printed by permission of Jon Harman, Ph.D. author.