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Apart from random noise, an atomic force microscopic (AFM) image may also suffer from an inclined plane owing to the in-coincidence between the scanning plane and the sample plane. While the wavelet-shrinkage-based image denoising technique was applied to remove the noise in the AFM image, the least-square-fitting technique was applied to the approximate sub-image so as to emendate the inclined plane. By using this method, the image de-noising and incline emendation can be implemented in parallel. As incline emendation was implemented in the approximate sub-band, the time cost for incline fitting is greatly reduced, and hence the real-time performance of the algorithm is improved. In addition, as the algorithm was implemented by means of wavelet transform, it can be easily combined with the wavelet-based image compression, which is beneficial to in-situ analysis and processing of AFM images. Through experiments, the new method was evaluated by employing an AFM image and the results were given and discussed.