A new type of ceramicbased porous composite material is used to bond structural members. When the ultrasonic Cscan system is used to detect the debonding defects of the components, the ultrasonic data produces strong acoustic noise due to the porosity and anisotropy of the material, resulting in blurred edges on reconstructed images. Aiming at this problem, this paper proposes to use the method of wavelet packet timefrequency domain analysis and energy spectrum analysis to obtain the spectrum and energy spectrum characteristics of ultrasonic echo signals. In order to enhance the characteristics of the echo signal, an adaptive wavelet packet threshold algorithm is used for noise reduction. Compared with the traditional ultrasonic denoising method, the signaltonoise ratio is increased by nearly 20%, which effectively reduces the interference of the noise signal to the original ultrasonic signal. On this basis, the image reconstruction of the tiny adhesion defects on the near surface of the ceramic substrate is performed, which achieved a clear characterization of debonding defect with a diameter of 2 mm. The results show that the effectiveness of the method proposed in this paper, the quality of the reconstructed image is greatly improved, and the edges of small defects are more clearly reflected, thereby improving the accuracy of quantitative representation.