During the past decade, small-footprint full-waveform lidar systems have become increasingly available, especially airborne. The primary output of these systems is high-resolution topographic information in the form of three-dimensional point clouds over large areas. Recording the temporal profile of the transmitted laser pulse and of its echoes enables to detect more echoes per pulse than in the case of discrete-return lidar systems, resulting in a higher point density over complex terrain. Furthermore, full-waveform instruments also allow for retrieving radiometric information of the scanned surfaces, commonly as an amplitude value and an echo width stored together with the 3D coordinates of the single points. However, the radiometric information needs to be calibrated in order to merge datasets acquired at different altitudes and/or with different instruments, so that the radiometric information becomes an object property independent of the flight mission and instrument parameters. State-of-the-art radiometric calibration techniques for full-waveform lidar data are based on Gaussian Decomposition to overcome the ill-posedness of the inherent inversion problem, i.e. deconvolution. However, these approaches make strong assumptions on the temporal profile of the transmitted laser pulse and the physical properties of the scanned surfaces, represented by the differential backscatter cross-section. In this paper, we present a novel approach for radiometric calibration using uniform B-splines. This kind of functions allows for linear inversion without constraining the temporal shape of the modeled signals. The theoretical derivation is illustrated by examples recorded with a Riegl LMS-Q560 and an Optech ALTM 3100 system, respectively.