Why digital enhancement of rock-art works:
rescaling and saturating colours

Bruno David, John Brayer, Ian McNiven & Alan Watchman 

Introduction
Rock-art holds a unique place in world archaeology.  While, like all artefacts, it is a product of cultural practice, rock-art has singularly been the source of a wide range of interpretative frameworks, from hunting magic (e.g. Breuil & Lantier 1965), to Leroi-Gourhan’s (e.g. 1968) structuralism, to diverse theories of style (e.g. Conkey 1990).  As a result of its continued significance in the development of archaeological theory, rock-art has come powerfully to influence how we approach social process and social experience (e.g. Rainbird in press), religion (e.g. Whitley et al. 1999), symbolism (e.g. David in press), humanity, cognition and language (e.g. Davidson 1991; Mithen 1996), ideology and culture (e.g. Mori 1992), aesthetics (e.g. Bahn & Vertut 1988), hegemony, resistance and the politics of place-making (e.g. David & Wilson in press), identity, representation and post-colonial theory (McNiven & Russell in press), culture contact (Frederick 1999), social landscapes (e.g. Bradley 1997) and inter-regional relations (e.g. David & Chant 1995) in prehistory.
Yet rock-art research is faced with a very real problem.  Like other items of material culture, rock-art is subject to various forms of destruction over the long term.  Such problems include granular disintegration of decorated rock surfaces; varied biological problems such as lichen, algal or fungal growths, insect nests and the rubbing of cattle against rock walls; water damage; graffiti; and the accumulation of dust mantles and other mineral crusts over rock surfaces.  The result is an increasing visual obstruction of the art through time.  These problems are so acute that significant proportions of pictographs in many art sites around the world remain too unclear to adequately record, their forms often being relegated to the general category ‘indeterminate’.  In Australia, this problem is well illustrated by various recording programs in the tropical north.  On the granite boulders of Torres Strait, exactly 50% of pictographs were identified as indeterminate by Ian McNiven et al. (2001); and in Australia’s Cape York Peninsula, 39% are indeterminate on the granites near Yarrabah (David 1994); 30% on the granite boulders of Bonney Glen Station (David 1991); 22% in the Mitchell-Palmer limestone zone (David, unpublished data); and 10% on the Ngarrabullgan sandstones and conglomerates (David 1992).  In the vast majority of cases, it is fading (caused by a variety of processes, see below) that has rendered the motif forms indeterminate.
The problem of image indeterminancy is particularly problematic in research projects that aim to investigate from the archaeological record temporal trends in social and cultural practices, for it is often the older art that has become most obscured.  The propensity for image obstruction through weathering or erosion, or through additive processes such as the deposition of mineral crusts, severely limits our ability to investigate temporal trends in rock-art through time as access to older motifs may be much restricted except in exceptional circumstances such as some deep cave contexts.  No rock-art has yet been found in deep caves in any part of tropical Australia, despite the hundreds of thousands of pictographs known in more open settings.
Numerous archaeologists are now using digital enhancement techniques to help them better see the rock-art that is or was once obvious on rock walls.  Relatively cheap yet powerful computer enhancement programs such as Adobe Photoshop or Corel Graphics are now easily available over the counter, ideal for rock-art applications.  Yet few archaeologists understand why enhancement works – what happens when an image is enhanced – or how far enhancement can be taken.  Phil Clogg and Margarita Díaz-Andreu (2000:842) recently noted that ‘To achieve the best results from image processing it is necessary to have not only an understanding of the nature and quality of digital imaging, i.e. resolution, grey (or colour) scale range, but also to have some knowledge of how the different processing functions operate’.  The aim of this paper follows this conviction by explaining why digital enhancement of rock-art works.  We use one of our own case studies from the islands of Torres Strait, between Australia and New Guinea, to illustrate two methods of image enhancement  colour rescaling and manipulation of colour saturation  to increase the visibility of rock-art images to the human eye.  We note from the onset that each rock-art panel, and each pictograph, presents a unique situation that may benefit from experimentation with a range of digital image processing techniques.  But there are some general principles that are broadly applicable and from whose understanding we can benefit from.  It is in this context that this paper is presented.
Why digital enhancement works
What is light?
Light travels through space as electromagnetic waves of varying length.  The entire spectrum of wavelengths is called the electromagnetic spectrum, but only a small section of this spectrum is capable of producing visual sensation.  Other parts of the spectrum include the longer wavelengths of radio waves up to the shorter infrared wavelengths that have wavelengths longer than visible red light, and ultraviolet light that has wavelengths shorter than visible violet light.  Despite some experimental efforts to use these non-visible wavelengths of light to record rock-art images, results have been mixed and by far the majority of recording is accomplished using visible light recording methods.  In any case, the general ideas of enhancement discussed here also apply to non-visible light.  Light can thus be defined as ‘radiation capable of stimulating the eye to produce visual sensation’ (Jacobson et al. 1988: 8), and relates to a narrow range of the family of electromagnetic wavelengths.
What is colour?
The human retina contains millions of light-sensitive cells that we may conveniently divide into two major types, rods and cones.  Rods are highly sensitive to light, cones less so.  Through variations in chemical composition, three types of cones enable us to discriminate between different colours; rods do not discriminate between colours.
The light that reflects off any surface (e.g. a rock background or a painting) consists of a ‘rainbow’ or spectrum of electromagnetic waves of different wavelength (e.g. red, yellow, green, cyan, blue, magenta).  These surfaces differ in colour when the reflected light has different amounts of light intensity in different parts of the spectrum, i.e. at different wavelengths (Figure 1).  A red surface has more intensity in the red wavelengths. A blue surface has more intensity in the blue wavelengths.  
How is colour measured?
A camera (both photographic and digital) records the amount of light reflected from each point of a surface using three different sensors, each sensitive to a respective colour, called red, green and blue (R, G and B). Three sensors are considered adequate because they are roughly equivalent to the way the human eye perceives colour using its three different types of cone receptors in the retina.
What is colour space?
So three numbers, R, G and B, the amounts measured by the three camera sensors and representing respectively the amounts of red, green and blue light at a point, determine the colour at a point in the image (i.e. a pixel or picture element).  Each image pixel is a tiny square, and each pixel colour can be considered a point in a three-dimensional ‘colour space’ whose coordinates are red, green and blue (Figure 2).  A colour point is characterised by its coordinates in 3D colour space (R, G, B). Colour intensities are frequently scaled between 0 and 1 and the colours at the corners of the ‘colour cube’ are the ‘primaries’, Red, Green and Blue, and the ‘secondaries’, Cyan, Magenta and Yellow.  Virtually any colour can be generated from a combination of the three primaries, including the secondaries themselves.  The line from Black to White along the diagonal of the colour cube is called the ‘grey line’ and consists of all shades of grey from black at the origin to white at the far diagonal corner.  Two colours nearby each other in colour space will appear similar.  Points in colour space near the grey line appear greyish or pastel or unsaturated.  The less grey is contained within a colour, the more that colour can be said to be saturated.  So colours near the three primary corners of the colour cube appear deep and pure and are called saturated.  This is a useful point to remember when digitally enhancing colour images, for minimising the proportion of grey within selected colours may increase the purity and thus the distinctiveness of the targeted colours.  A non-selective saturation of all colours in an image may bring out the distinctiveness or contrast of all coloured pixels and thus coloured regions within the image.  And likewise, maximizing the amount of grey can desaturate background colours on a surface and make it appear more uniform.
What are some of the ways to represent a colour in colour space?
There are several equivalent ways to represent colours.  These ways are essentially different coordinate systems for colour space analogous to cylindrical, conical or spherical coordinates for 3D positions in surveying.  Two of the more important ones are discussed below. 
In the R, G, B system, we use the measured coordinates (R, G, B) directly. The resulting colour coordinates are rectangular and the colour space is a cube. These coordinates correspond directly to the physical light measurements made by the camera.  They are easy to use and easy to understand.  However, they are not always the most intuitive to use for certain types of colour manipulation and enhancement.
In the H, S, B (or H, S, L) system, the coordinates are essentially a 3D conic coordinate system for 3D colour space (Figure 3).  H is the ‘hue’, or dominant spectral wavelength of the colour. Hue, H, is an angular coordinate around the circumference of the conic colour space.  The hue identifies the colour – green, yellow and so forth – wavelengths typically between 400 and 700 nanometres along the electromagnetic spectrum.  The hue thus identifies the spectral quality of a visual sensation.  S is the saturation of the colour, that is, the ‘purity’ of the colour or the extent to which other colours are mixed into the dominant wavelength.  Pure red is saturated, but pink is unsaturated because it has white (a combination of all colours) mixed in.  Saturation, S, is a radial coordinate, measuring distance away from the centreline of the conic colour space, which is oriented along the grey line.  B is the ‘brightness’ or lightness (L) or total intensity of the colour.  It refers to the amount of incident light a colour reflects.  Brightness, B, measures the distance along the axis of the cone (the grey line) away from the origin of colour space (the point representing the colour black).  Artists and image enhancers use the (H, S, B) system because the intuitive meaning of the coordinates frequently matches the manipulations they wish to apply.
What is the colour space representation of a group of similar colours?
If we look at the colours of a group of pixels from a region of an image, they are frequently similarly coloured. For example a blank background area of rock has a texture of similar colours. When these similar colours are all plotted together in colour space, they produce a ‘cloud’ or distribution of colour points, one for each pixel (Figure 4). Here, for convenience, we show the colours of the pixels in the 2D projected red-green subspace of the full 3D colour space.  So in this projection, the grey line projects onto the yellow line which is the (upward to the right) diagonal in Figure 4.
What is the colour space representation of 2 differently coloured regions?
If we now look at an additional group of pixels, for example selected from a foreground figure region of the image, these pixels will also be coloured similarly to one another, forming a cloud or distribution of points in colour space. However, these points should be coloured differently from background pixels. So this cloud of points should be separated in colour space from the cloud of background colours (Figure 5).
What is contrast?
If the colour clouds of different image regions are widely separated in colour space, we say the image has good ‘contrast’. If the colour clouds of image regions are close together or even overlapping in colour space, we say the image has poor contrast.  So contrast is a measure of how spread out in colour space the image colour points are. We usually express contrast in qualitative rather than quantitative terms.  So we talk about ‘good’, ‘poor’ or ‘better’ contrast, but usually do not attach a quantitative measure to the amount of contrast.
What is fading?
Rock art images generally start out having good contrast, but over time, by a variety of processes, the images undergo the process of ‘fading’, which tends to reduce the contrast between foreground figures and the background rock.  The process of fading tends to move the colour distributions closer to one another and closer to the grey line so that differences may eventually disappear.  Sometimes, the colour differences do not totally disappear in an image, but just become not noticeably different.
What are the minimum colour differences that can be perceived?
Different coloured pixels are different points in colour space. If colours are more distant from one another in colour space, they will look more different in the image. If colours are close to one another in colour space, the differences may not be ‘noticeable’ by a human observer. Colour scientists define the term, ‘Just Noticeable Difference’ to mean the distance apart two colour points must be in colour space for the colours to be just barely noticeably different. This is the distance in colour space at which the difference just becomes perceptible by a human viewer. So for any given reference colour, all other colours nearby will be ‘Not Noticeably Different’. Colours farther away in colour space will be ‘Noticeably Different’ (Figure 6).
Why does image enhancement work?
‘Contrast enhancement’ is a process in which we transform the colours of all the pixels of an image to try to increase the distance in colour space between the colour clouds of the foreground and background pixels. If we do it correctly, we can convert differences that are not noticeably different into differences that are noticeably different.
What are some of the ways to do contrast enhancement?
There are several ways to accomplish colour contrast enhancement. The basic difference between the different ways of enhancement is that they expand the colour differences in different directions in colour space. One way is simply to ‘re-scale’ one of the basic colour coordinates, red, green or blue (Figure 7). This expands colour points parallel to one of the Red, Green or Blue axes.  For example, in Figure 8a we present a green background with a green-slightly red star in it.  The amount of red in the star is very slight, so it can barely be discerned from the background with the naked eye.  By rescaling (increasing) the proportion of red in the entire image, the background stays green (for it does not contain any red), but the star is enhanced, turning yellow (Figure 8b). 
Another way to enhance is to represent the colour coordinates in terms of hue, saturation and brightness (H, S, B).  Then saturation represents the distance of a colour from the centre of colour space (the grey line). By increasing the saturation of colours, we move the colours proportionately radially away from the grey line, increasing the distances between colours (Figure 10). 
These two techniques, increasing contrast by colour rescaling and altering the saturation of colours, are usually undertaken manually.  However, it is worth noting that there are also sophisticated statistical techniques that compute the centres and shapes of the foreground and background clouds and then rescale all the image colours to maximize some mathematical distance between the clouds. 
None of the above methods is always inherently better than another, and indeed various combinations often prove to produce the best results. A method’s performance depends upon the particular image being enhanced and its particular colour cloud distribution. The performance is usually evaluated by human perception so the different enhancement methods must be evaluated and modified interactively.  For these and other reasons, simple methods such as colour rescaling and enhancing colour saturation tend to be used more frequently than other, more complex methods.  And because many different enhancements can be evaluated quickly and intuitively, these simple methods frequently produce very good results.  Fast and easy interaction and observation of the results is the great benefit of an image enhancement application program such as Adobe Photoshop or Corel Graphics.
Finally, we end this section with a word of caution.  While digital enhancement promises to revolutionise rock-art research, it is also important to understand that the results of digital image enhancement can be misleading and should be viewed with a healthy dose of skepticism.  Results are frequently presented as a single image in which desired artefacts mysteriously appear from out of the noise.  While such a result is indeed common, it is also possible that the artefact is a creation of the processing itself and is not in fact part of the original art.  It is at best difficult and often impossible for the viewer of a single image to evaluate which is the case.  For this reason, it is imperative that original (non-enhanced) images are presented along with the enhanced versions, and that we are told precisely the processes that have been followed when enhanced images are published, in particular to determine whether or not particular sections of an image have been preferentially enhanced.
The investigator doing the enhancement is usually in a better position to evaluate the validity of the enhancement because s/he is able to view many different enhancements of the same image.  But even s/he frequently finds it impossible to determine the validity of an enhancement.
We believe strongly in the use of these techniques in the field, using digital cameras and laptop computers, so that results may quickly and interactively be checked against the actual rock surface.  But in the end there may still be some doubt about the reality of an enhancement.  Digital image enhancement is not a miracle weapon in rock-art interpretation.  It is simply one more powerful tool provided by technology that may be properly or improperly used.  The responsibility for proper interpretation still lies squarely on the shoulders of the investigator.  A better understanding of the processes underlying digital image enhancement will help investigators make better judgments about when the application of this technique is warranted. 
Enhancing the rock-art of Torres Strait
Let us now apply these principles to one rock-art site in Torres Strait, the objective being to reveal previously unknown, faded pictographs to resolve or address long-standing archaeological questions.  
Torres Strait is a 150km-wide watery realm separating the Australian and New Guinean mainlands. It is home to ‘Torres Strait Islanders’ who, like their ancestors, harvest the seas for fish, turtle and dugong. On some islands, population densities of over 100/km2 existed at the time of initial European contact, which is an order of magnitude greater than the highest densities documented for Aboriginal Australia.  Globally, Torres Strait is most famous as the place where the Melanesian and Australian (Aboriginal) cultural and ecological domains meet and as a transition zone between the horticultural and hunter-gatherer worlds (Harris 1977). Coring of reefs and islands reveals the Straits were established 8000-7000 years ago and that island formation is ongoing (e.g. Barham 2000). Thus, Islander society must have developed within this period and functioned as a bridge and barrier for diffusion of cultural traits (and flora/fauna) between NE Australia and Melanesia (Walker 1972).
Little is presently known of the nature of interaction between Australia and New Guinea, via Torres Strait, in prehistory.  One avenue of research is through the rock-art, investigating spatial and temporal trends in artistic conventions.  Unfortunately, much of Torres Strait’s rock-art is faded, and in many instances only the most recent artistic phases appear to have survived.  In some cases, however, bare traces of earlier art, sometimes superimposed by more recent pictographs, are apparent, although the shapes of individual motifs are too obscure to be determined with the naked eye.  In such cases, digital enhancement offers promise for the recovery of images.  We illustrate here such recovery through the selective enhancement of colour saturation and colour rescaling at the site of Kabadal Kula on the island of Dauan (see McNiven et al. [2000] for details of the site’s significance).
Kabadal Kula
Oral tradition indicates that the most recent phase of rock painting at Kabadal Kula likely took place during a head-hunting raid from southern Papua in the mid-19th century CE.  The paintings then-undertaken appear relatively clear, but faint traces of earlier artistic episodes were barely visible at the site at the time of recording in April 2000.  The motifs purportedly associated with the most recent phase have obvious associations with southern Papuan artistic conventions, including clan designs.  A vexing question in Torres Strait prehistory has long concerned the antiquity and nature of interactions with Papuans, and towards this end we were curious to identify the more faded and apparently older motifs at Kabadal Kula.  
The site was systematically photographed with two Nikon Coolpix 950 digital cameras by the authors. We initially undertook a series of test photographs of various parts of the granite wall so as to obtain a preliminary indication of the rock-art’s potential for computer enhancement. Upon return to the office of the Island Council on the first evening of fieldwork, the digital photos were enhanced using Adobe Photoshop 5.0, revealing paintings in parts of the rockshelter where none were evident with the naked eye, and where faint traces of red pigment were evident.  The locations of these decorated parts of the shelter wall were noted, and the following day the entire rock surface, from one end of the shelter to the other, was systematically photographed with the digital cameras in a series of 14 overlapping panels, irrespective of whether or not rock-art was apparent on the rock wall (Figure 13).  Both cameras were used independently of each other, resulting in two sets of similar but not identical photographic coverage. Photographs were taken both with and without standard IFRAO photography scales (the scales were never adhered to the rock wall, but held by one member of the recording team adjacent to the part of the rock wall targeted for photography).  Every visible item of rock-art was photographed individually, and photographs were also taken of sets of adjacent rock paintings as well as of broad sections of painted rock wall. A total of 359 digital images were taken at the site. 
Sixteen out of a total of 44 pictographs at Kabadal Kula were clear enough to the naked eye to make out their motif forms.  Seven previously unknown, faded motifs were revealed by re-scaling and saturating colours (16% of the art at the site).  At least some of these faded motifs appear to represent the earliest artistic phase(s) at the site, the timing of which we aim to further investigate through forthcoming excavations (to obtain discarded pieces of ochre datable through stratigraphic association).  The seven newly revealed images include a ‘face’ or ‘mask’ and an adjacent shield reminiscent of Papuan forms (shields are not known from Torres Strait ethnographically; this image may therefore signal Papuan cultural influences predating the ethnographic situation) (Figure 10); an anthropomorph and a shark head-dress akin to those recorded by Haddon (e.g. 1935) during the Cambridge Expedition to Torres Straits in 1898 (Figures 14 & 15); an insect-like figure (Figure 16); a face or mask following Papuan conventions (Figure 17); and what appears to be a claw-sail canoe typical of the region to the immediate east (Figure 18).  None of the underlying art is reminiscent of Austronesian conventions, so common today as during much of the late Holocene in Island Melanesia to the east and northeastern Indonesia to the west.  The implication of the rock-art conventions evident in Torres Strait’s faded paintings is that Papuan influences in Torres Strait, to the exclusion of Austronesian influences, may have some antiquity, in support of recent models of Islander prehistory recently formulated by Tony Barham (2000).
The faded rock-art of Kabadal Kula was revealed using various methods of digital enhancement; those shown here represent the best results, obtained simply by saturating all colours; or by selectively saturating the reds (colour of the pictographs) and completely desaturating all other colours; or by rescaling all colours parallel to one of the colour axes. 
Conclusion
The florescence of rock-art research that began in the 1980s continues into the 21st century, not least due to the emergence of new dating and digital enhancement techniques enabling its characterisation in time and space.  The wide range of environmental and technical contexts of rock-art production, including the geology of the rock surface, sources of erosion, human pressures on the art’s survival, rock-art techniques and pigment types will always mean that the best digital enhancement techniques for any given situation will require a combination of general principles and unique address.  
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