In this paper, we introduce a new algorithm that can be used for reducing aliasing in images. Our algorithm, which is derived from the standard diffusion equation, cancels the aliasing of step edges found in images by reducing their curvature while preserving their contrast through a high-pass filter. Our algorithm can be seen as an adaptive level-curve method in which diffusion is carried out in the normal direction of the gradient. Experimental tests based on different grey-level images show that our algorithm efficiently reduces aliasing, which is confirmed through objective and subjective quality evaluations.