Comments on Revision Technique in Cubic B-Spline SmoothingAn Inverse Diffusion Restoration Understanding
样条磨光的盈亏修正技术与图像反扩散恢复

The profit-and-loss revision technique may improve the accuracy of approximation to raw image data undergone a cubic B-spline smoothing. Comments are made on this technique from the viewpoint of image smoothing and restoration, giving highlights on the equivalence between spline smoothing and diffusion smoothing, and between profit-and-loss revision and inverse diffusion restoration; formulating the revision operators into a series of renewal recursions together with an estimation to the order of their deviations from the raw data; and exposing the numerical instability of both simple and renewal recursion of the profit and loss revision. Finally, a discussion is further made on the feasibility of applying the profit-and-loss revision to edge detection for images in the presence of noise.