Many camera calibration methods for a non-metric digital camera have been proposed. Most of them adopt polynomials of image coordinates composed of terms representing the correction to the principal distance, the offsets of the principal point, the radial lens distortion, and the decentering lens distortion of the target camera as the image distortion model in the calibration. However, few reports on selection of unknown parameters of the image distortion model in the calibration evaluate an estimated distribution of image distortion directly. Therefore, we conducted a numerical simulation on selection of unknown parameters of the ordinary image distortion model widely used for camera calibration. Evaluation of calibration results was performed by differences of image distortions calculated at all pixels on the image between the obtained image distortion model and the setup one. The simulation results indicate that an image distortion model without the terms representing the decentering lens distortion of the target camera in the calibration cannot necessarily provide a reliable distribution of the image distortion. The authors propose selecting all parameters of the widely used image distortion model as unknowns in the camera calibration.
The effects of changes in DEM resolution on Japanese mountain topography are examined from the viewpoints of geomorphometry. First, in order to examine the influence of resolution on the histogram of slope angles, the changes in the descriptive statistics value as a function of resolution are plotted. As a result, DEM with 25-m resolution or more high-resolution DEM should be used when calculating slope angles. Next, we examined the appropriate resolution from the viewpoint of magnitude frequency distribution of landslides that greatly contributing to slope formations in Japanese mountains. From this examination, it was clarified that 5 to 10-m resolution DEM is needed to observe slope forms in and around landslide area. However, more high-resolution DEM is preferred to analyze the detail of landslide topography. At last, we evaluate the effects of DEM resolution using the accuracy of drainage network construction. We could judge that the 10-m DEM is enough to extract the drainage network for practical applications. From these results, we need 25-m DEM at least, and about 5 to 10-m DEM ideally for geomorphometry in Japanese mountains. Therefore, it is desired to be equipped with around 5 to 10-m DEM acquired by direct measurement for geomorphology.
An objectoriented method has been recognized as superior to a pixel based method in land cover classification using high resolution satellite images (e.g. IKONOS, QuickBird) . Accurate objectoriented land cover classification is premised on precise image segmentation. Many region-growing methods are suggested and applied to improve the image segmentation. However, most of them do not have an objective criterion to decide the segmentation scale. This study inquires an objective and convenient method to optimize the regiongrowing image segmentation. The observation toward process of region-growing has showed the impracticality of using single common threshold over the whole scene. We suggest a method to extract the optimal regions by detecting the earliest stable stage of region-growing in every pixel. The evaluation (comparing the result with conventional regiongrowing method) has pointed out the effectiveness of the method for image segmentation as follow. This method can 1) restrain over-segmentation, 2) extract image objects with low coefficient of variation, 3) eliminate the subjectivity of the operator's work and 4) decrease the work load by its automatic algorithm.