This paper proposes a tomographic short-time integral imaging method. In terms of terahertz tomography, the experimental results show that the data quality and imaging effect of the proposed short-time integral imaging method are better than those of the traditional method. In the wavelet denoising theory, a δ-σ evaluation rule is proposed based on the characteristics of the terahertz signal, and the optimal wavelet denoising combination (e.g., the sym7 wavelet with a decomposition scale of 5) is selected using the evaluation rule. Based on this, the short-time integral imaging experiment of nondestructive detection tomography of phenolic plastic samples is set up, and different wavelet denoising combinations are compared. The effect of wavelet denoising is compared from two subjective evaluation indexes of defect number and defect recognition rate and the objective evaluation index of Weber contrast. Results prove that the sym7 wavelet (with the decomposition scale of 5, soft-threshold processing) is effective in wavelet denoising of nondestructive detection signals of phenolic wedge defects. The background noise in the nondestructive detection image of the sample after signal preprocessing is effectively suppressed. The contrast effect between prefabricated defects and the background area is more obvious, and the internal structural changes in the sample can be detected easily and accurately.