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The object of this dissertation is the defrosting video of single air-conditioner. Based on the changes of image gray, frost-defrost process time series data is obtained. Then, fogging noise data smoothing is mainly studied. A method of setting synchronous sampling contrast area is proposed. Contrast region is used to monitor fog’s appearance and dissipation, and then fog existence intervals are recognized and oriented. Based on linear interpolation method, inner data within the relevant intervals of frost curve can be adjusted through interpolated reconstruction. By above means, the fog noise of process data can be removed, and data without fog noise can be unaffected. At last, some applicable conditions are provided. Experiments show that the algorithms based on contrast area setting can obtain good curve smoothing results. The principle of this method is simple, and it has a good effect of filtering and smoothing of the data curve. In the field of curve smoothing, it has some application space.