Hemispheric image processing with the goal of solar radiation determination from ground-based fisheye images is a valuable tool for silvicultural analysis in forest ecosystems. The basic idea of the technique is taking a hemispheric crown image with a camera equipped with a 180°fisheye lens, segmenting the image in order to identify solar radiation relevant open sky areas, and then merging the open sky area with a radiation and sun-path model in order to compute the total annual or seasonal solar radiation for a plant. The results of hemispheric image processing can be used to quantitatively evaluate the growth chances of ground vegetation (e.g., tree regeneration) in forest ecosystems. This paper shows steps towards the operationalization and optimization of the method. As a prerequisite to support geometric handling and georeferencing of hemispheric images, an equi-angular camera model is shown to describe the imaging geometry of fisheye lenses. The model is extended by a set of additional parameters to handle deviations from the ideal model. In practical tests, a precision potential of 0.1 pixels could be obtained with off-the-shelf fisheye lenses. In addition, a method for handling the effects of chromatic aberration, which may amount to several pixels in fisheye lens systems, is discussed. The central topic of the paper is the development of a versatile method for segmenting hemispheric forest crown images. The method is based on linear segmentoriented classification on radial profiles. It combines global thresholding techniques with local image analysis to ensure a reliable segmentation in different types of forest under various cloud conditions. Sub-pixel classification is incorporated to optimize the accuracy of the method. The performance of the developed method is validated in a number of practical tests.