In this paper, a new inspection method, joint scanning laser thermography (JSLT) as well as its data reconstruction and processing algorithm, is proposed. The new inspection method is utilized to detect and characterize the flat-bottom holes (FBH) in carbon fiber composites by using joint laser scanning scheme. By analyzing the nature of the thermal image sequences sampled under such a scanning scheme, a quick and simple reconstruction method is developed to characterize the buried depth of defects based on 1D heat conduction model. The processed thermal images are expected to get higher temporal resolution and spatial resolution. It can inspect larger area within shorter acquisition time than the pulse thermography. Thus, the study solves the dilemma between the inspection speed and the inspection capacity. Later, a joint laser scanning thermography test is set up to test the algorithm on a carbon fiber composite panel with defects buried at different depth. The experimental results show that the reconstructed data almost behave as those under pulse excitation. The tendency of temperature to change in the logarithmic domain over time is similar to the curve in the TSR method. But, unlike the pulse thermography data, the defect detection rate of PCA based on reconstructed data is higher than that of fast Fourier transform (FFT) amplitude image, independent component analysis (ICA) and FFT phase image. The JSLT system is used to detect FBHs and the diameter-depth ratio reached 3.33.