Full waveform data decomposition is critical to obtain the effective information of tested object from the large-spot laser altimetry data. Gaussian decomposition and wavelet decomposition are two universal methods to achieve the full waveform data decomposition in the large-spot laser altimetry currently. However, the decomposition effect and accuracy are ambiguity for different echo signals of ground objects. In this paper, the two methods are applied to the full waveform data of the Geoscience Laser Altimeter System (GLAS), and the waveforms of several typical ground objects in flat and slop areas are decomposed. The results are analyzed and compared qualitatively and quantitatively according to the index of goodness-of-fit and the iteration times of achieving the best goodness-of-fit. The results show that the Gaussian decomposition and Guassian wavelet decomposition are nearly same for the accuracy of best goodness-of-fit. With the increase of the complexity of the ground objects, the iteration times of achieving the best goodness-of-fit with the Gaussian decomposition is less than that with the Gaussian wavelet decomposition.