Quality Comparison of Digital and Film-based Images for Photogrammetric Purposes
ISPRS Commission III: Theory and Algorithms, 2004
Digital cameras are replacing analog film not only on the consumer market. New digital aerial cameras such as Vexcel Imaging UltraCamD or Z/I DMC implement novel concepts that make the changeover to digital photogrammetry possible. The comparison of image quality of these sensors is important when switching from analog to digital. In this paper we propose algorithms of how to assess image quality, whereas the main focus is set to stereo matching which is the fundamental for several photogrammetric procedures, like generation of digital elevation models or true orthophotos. We use test image data from an experimental setup. We took images with a 11 megapixel CCD sensor and analog small format camera with several types of film. The focal lengths of the used lenses are chosen in that way, that a 9µm digital pixel (native CCD pixel size) represents the same object point as a pixel from a 20µm film scan. With this constellation we are able to show that the quality of a 9µm CCD pixels outperforms the quality of a 20µm or less scanned film pixel. The main disadvantage of analog film is its granularity that causes grain noise. To measure the impacts of grain noise to image processing tasks, we use the following algorithms on artificial and natural images: Distances to the epipolar ray of stereo matching results, Blonksi and Luxen edge response test, minimal radius of Siemens star and noise measurement via entropy. In contrast to film images that feature a dynamic range of 8 bit, images captured with digital sensors feature a high dynamic range of 12 bit and contain almost no noise. This makes the matching of poorly textured structures in digitally sensed images possible with high accuracy, even when the matching in conventional film images fails. Stereo matching on digital images results in a 2.5 times smaller noise level. The conclusion of the proposed work is that digital sensors are leading to highly accurate and robust photogrammetric processing.