Toward a Non-linear Grayscale Calibration Method for Legacy Photographic Collections

Introduction While a picture may say a thousand words, scientists and engineers often need to extract precise, quantitative information regarding physical processes from photographic evidence. Image analysis can, for example, be used as part of a quality control process in an industrial application, to monitor earth systems from space using satellite data, or to reconstruct changes in past climate from photographs of deep-sea sediments. How well questions related to each of these applications can be answered depends on a variety of factors, some of which can be easily controlled, others of which impose inherent tradeoffs, (for example the relationship between depth of field and focal length). Taken as a whole, these variables along with the hardware and software employed for capture, manipulation, and storage of the image compose the " total system response " or " lifecycle " of the image. Extraction of depth series of grayscale values from photographs of deep-sea sediments provides a means of characterizing the stratigraphy of marine sequences in fine detail. Relating these grayscale proxy records to specific sediment components can, however, be somewhat difficult. This difficulty can arise from several factors. Perhaps the most inherent of these difficulties is the fact that conversion of a colorful scene to monochromatic grayscale results in distortions of the original information in the scene. Consider for example, that different shades of color can have the same grayscale value leading to misidentification. A second concern is that differential wetness of the split core surface can result in variable amounts of specular reflectance from the core surface and thus contribute to variable glare within an image. The method thus works best in environments that are relatively monochromatic such as a binary mixing between terrigenous clay and marine carbonate. 2 Because sediment brightness is often controlled by sediment carbonate content, grayscale values are often interpreted in terms of sediment carbonate content. Attempts to relate the two variables quantitatively often prove to be difficult. One source of difficulty that must be addressed with this method is the need to intercalibrate grayscale values from photographs of cores in which lighting conditions and geometry may have differed. We explore a revised means of intercalibrating grayscale images that considers the nonlinearity inherent in the total photographic system response. Comparison of corrected grayscale values with measurements of sedimentary carbonate content by linear correlation indicates that the corrected grayscale values can be used to predict carbonate content …