Ultrasonic signals are widely utilized in the industry for detecting defects and material characterization. In this context, the Total Focusing Method (TFM) is commonly applied for post-processing of ultrasonic data. Those are acquired by phased array transducers through the Full Matrix Capture (FMC) technique. Although the FMC-TFM technique is widely employed, the energy of the wave transmitted to the material is limited by the utilization of a single element of the transducer, which can provide a low Signal-Noise Ratio (SNR) of the reconstructed image. To circumvent this limitation and enhance TFM image quality, this work proposes the use of the Virtual Sources technique combined with two different methods for SNR improvement: Decomposition of the Time Reversal Operator (DORT) and Spatially Averaged Sub-Aperture Correlation Imaging (SASACI). In the latter, we also propose modifications to make the original approach more robust. Both combinations were implemented, applied and evaluated for the enhancement of images for characterization of multiple defects. These proposals were all assessed through simulations and experiments. The simulations considered a finite element model of a steel block containing four holes emulating volumetric defects on the material. Several noise levels were added to the simulated signals aiming for performance assessment in an environment with high levels of non-correlated noise. The proposed combinations in the simulated FMC data showed that the utilization of the Virtual Sources technique combined with DORT increased the SNR up to 21.5 dB, while the combination of Virtual Sources with SASACI was capable of increasing SNR up to 76.2 dB. The second combination is 16.3 dB above the sum of the individual gains for each technique applied separately, while the first combination is 7.4 dB above. This implies a synergistic effect in the improvement of image quality for both proposed combinations. Moreover, the utilization of the Virtual Sources technique was capable of enhancing the reconstructed image, where it is not possible to initially distinguish the noise of the signal of interest. The experimental evaluation was realized on the four-hole steel block with the same properties of the simulated block. Unlike the simulation, the collected data were not subjected to high levels of noncorrelated noise. Thus, for both combinations, the utilization of the Virtual Sources technique did not result in significantly superior gains when compared to the individual gains obtained from each technique individually applied. The use of DORT and SASACI without Virtual Sources caused an SNR increase of 7.5 dB and 75.0 dB, respectively, while this increase was of 9.2 dB and 74.1 dB when the Virtual Sources was used in combination. The results obtained from SASACI, when compared to DORT, were evidently superior for both simulation and experimental evaluation. Both methods showed potential for improvement of TFM image quality, and thus, are promising for application in nondestructive evaluation.