## 4 Experimental Analysis and Discussion
### Analysis of Experimental Results  
For comparison, the sine-cosine transform average denoising method is also used to process these results and analyze the effect of the mask and iterations. The phase fringe patterns with different densities are processed by the sine-cosine transform average denoising method with mask sizes of 3 \(\times\) 3 and 27 \(\times\) 27 for five and fifteen iterations. The sparse fringes processing results using the sine-cosine transform average denoising method with different masks and iterations are shown in Figure 10. The denoising effect of sparse fringes becomes better by using the 3 \(\times\) 3 mask with increasing iterations, as shown in Figure 10b,c. A satisfactory denoising effect can also be achieved by using the 27 \(\times\) 27 mask with five iterations, as shown in Figure 10d. But more iterations will over-smooth the phase reversal information and lead to loss of details, as shown in Figure 10e. The execution time increases as the number of iterations increases regardless of the mask size, as shown in Figure 11a. The dense fringes processing results using the sine-cosine transform average denoising method with different masks and iterations are shown in Figure 12. A large amount of speckle noise still exists in the wrapped patterns with the 3 \(\times\) 3 mask and fifteen iterations, as shown in Figure 12b,c. The denoising result with the 27 \(\times\) 27 mask and five iterations is better than that with the 3 \(\times\) 3 mask and fifteen iterations, as shown in Figure 12d. However, the large-sized mask may deteriorate the quality of the wrapped patterns with increasing iterations, as shown in Figure 12e. The relationship between the calculation time and the number of iterations is shown in Figure 11b. Increasing the number of iterations with this small mask will lead to too much time and lower calculation efficiency. Figure 10: (**a**) Sparse shearography–interferometric phase fringe patterns; Filtered by different mask sizes for various iterations: (**b**) 3 \(\times\) 3 for five times; (**c**) 3 \(\times\) 3 for fifteen times; (**d**) 27 \(\times\) 27 for five times; (**e**) 27 \(\times\) 27 for fifteen times. Therefore, different masks and iterations must be considered for different snarography fringe phase patterns. Small-size masks are suitable for the high-density fringe pattern, and large-size masks are ideal for the low-density fringe pattern. The sine-cosine transform average denoising method is applied to process the fringe pattern with the consideration of the denoising efficiency caused by the iterations. The denoising effect does not operate well with too few iterations. If too many iterations exist, it is easy to cause over-filtering, adhesion, and low efficiency. In practical application, we need to select the size and shape of the mask and the number of iterations for a satisfactory denoising effect. The decomposition levels and the denoising threshold of the sine-cosine transform wavelet threshold denoising method in this paper are determined adaptively rather than through artificial arbitrariness. As shown in Figure 13, snarography-interferometric phase fringe patterns and speckle-interferometric phase fringe patterns are processed by the sine-cosine transform average denoising method and the sine-cosine transform wavelet threshold denoising method. The denoising effect is also shown in Figure 14.  
Figure 11: Execution time for the number of iterations from one to twenty: (**a**) sparse fringes; (**b**) dense fringes. Figure 12: (**a**) Dense snarography–interferometric phase fringe patterns; Filtered by different mask sizes for various iterations: (**b**) 3 \(\times\) 3 for five times; (**c**) 3 \(\times\) 3 for fifteen times; (**d**) 27 \(\times\) 27 for five times; (**e**) 27 \(\times\) 27 for fifteen times. method, respectively. The appropriate mask and iterations are selected to achieve satisfactory filtering results for the sine-cosine transform average denoising method.