Saturation And Value Modulation (SVM): A New Method For Integrating Color And Grayscale Imagery

Algorithms for integrating color imagery with grayscale imagery have long been an important feature of many remote sensing (RS) image analysis and geographic information systems (G S). Traditional methods for data integration include Red-Green-Blue (RGB) /Hue-Saturation-Value (HSV) transformation and RGB modulation. However, these techniques are either inflexible or present a compromise between the quality of the color and the contribution of the shading. Furthermore, these techniques can also result in serious color distortions. Layer transparency is another popular technique for integrating data that is available in most RS and G S software packages. However, optimal integration of color and grayscale imagery is difficult to achieve using this method. We briefly review the shortcomings of these traditional image integration methods and introduce a new method (Saturation-Value-Modulation [SVM]) for raster image integration developed by David Viljoen at the Geological Survey of Canada. SVM is flexible and does not compromise the color or grayscale components of the resulting integrated image. The general concepts behind this algorithm as well as the five parameters used to control the integration process are discussed. Various examples of how SVM can be used to integrate various geoscience data are also presented. Finally, we provide a brief overview of the ESR ArcG S implementation of SVM, though we do not include a detailed presentation of the actual Visual Basic code or the algorithm. The ArcG S map document (MXD) that contains the VBA (Visual Basic for Applications) code is available for download for those who wish to use SVM.