This paper presents tests of a new approach for the correction of image inhomogeneities directly from the corrupted image data.The distortion of the image brightness values by a low-frequency bias field often occurs in MR imaging and impedes visual inspection and intensity-based segmentation. The inhomogeneity problem is even more pronounced in surface-coil images. The new correction method is based on a simplified model of the imaging process and the inhomogeneity field. The appropriateness of a polynomial model of the bias field in MR imaging is tested by analyzing the MR images of a phantom with known ground truth. The new bias correction scheme has been applied to large series of 2D and 3D MRI image data sets as well as to different types of synthetic images, demonstrating the robustness and generic nature of the algorithm. This paper additionaly contains two sections about the apropriate choice of parameters for the correction.