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One of the challenges in the development of photon counting spectral computed tomography (CT) detectors is that the location of the energy thresholds tends to vary among detector elements. If not compensated for, this threshold variation leads to ring artifacts in the reconstructed images. In this paper, a framework is presented for the systematic comparison of different methods of compensating for inhomogeneities among detector elements in photon counting CT with multiple energy bins. Furthermore, we propose the use of an affine minimum mean square error estimator, calibrated against transmission measurements on different combinations of two materials, for inhomogeneity compensation. Using the framework developed here, this method is compared to two other compensation schemes, flatfielding using an air scan and signal-to-thickness calibration using a step wedge calibrator, in a simulation study. The results show that for all but the lowest studied level of threshold spread, the proposed method is superior to signal-to-thickness calibration, which in turn is superior to flatfielding. We also demonstrate that the effects of threshold variation can be countered to a large extent by substructuring each detector element into depth segments.