以三阶B－样条作数据摩光时，引入盈亏修正可以在磨光的同时提高逼近原始数据的精度,通过从图象的平滑与恢复处理的角度出发来对盈亏修正技术进行评注，并进一步阐明了样条磨光与扩散平滑、盈亏修正与反扩散恢复在离散条件下的等价关系，给出了用于修正的更新迭代算子序列以及相应的偏差附数估计，并助指出了盈亏修正的简单迭代和更新迭代都是数值上绝对稳定的计算；最后讨论了盈亏修正技术在图象边缘探测中的适用性。

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.