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In this paper the method of multidimensional (n-D) filtering based on prior signal integration is analyzed. This method has the advantage that the computational complexity for filtering is independent of the filter kernel size. An overview of recent 2-D image processing systems is presented where these types of filters are applied. Based on this overview a framework that covers this class of filters is derived using repeated integration. These filters include for example rect and triangle-filters which can be used to approximate Gaussian derivative filters. Furthermore the normalization of the filters, computational complexity, and storage cost are discussed. Finally, two image processing systems which benefit from the application of the filters are presented. They belong to the topic of advanced driver assistance systems.