In this study, the grayscale characteristics of plasma spots are analyzed. First, the L component of the original spot images is extracted based on the principal component combined with mask processing in the HSL color space. Thus, effective grayscale images can be obtained with a high signal-to-noise ratio. The average grayscale curves of single spot image are analyzed before and after processing, and the grayscale curves of the original spot images contain several burrs, whereas those of the processed image are smoother. Second, by extracting the grayscale feature of the spot sequence images, the graysale value of the spot sequence images can be observed to change periodically with the reciprocating ablation motion of the femtosecond laser beam. Third, a method that combines fractal interpolation with wavelet transformation is used for processing the average grayscale characteristic curves of the spot sequence images. This method not only keeps the detail information of the average grayscale characteristic curve clearly, but also makes the curve smoother. Finally, by analyzing the correlation between the spot grayscale characteristics as well as the ablative processing power and the movement of the processing platform, a strong correlation can be observed between them. Thus, this study provides a significant basis for adjusting the laser power and obtaining the processing-depth feedback of microstructures based on the spot grayscale index.