In this paper, an inspection system has been presented that uses Laser-Ultrasound (LU) technique for Nondestructive testing (NDT) of metallic structures with specific interest in Oil & Gas sector. While the developed system is the first one of its kind in the Middle-Eastern region, the nature of signals are quite unique as well and traditional signal processing runs into a lot of algorithmic complications with them. A new approach has been developed for this setup in order to efficiently enhance signal to noise ratio for the underlying signals so that any subsequent classification/intelligent-detection system can be based on the outcomes of this algorithm. Multiform Tiltable Exponential Distribution (MTED) kernel, which is a generalization of 2<sup>nd</sup> order Cohen's class functions in Time-Frequency Representation (TFR) space, has been used in this work to isolate the essential frequency components with temporal and frequency based masking filters. By using this technique, we were able to isolate many significant defects buried in heavy noise and correlating signals. This enables the identification of the defect wavelets as well as their locations can be identified from the ambiguous and contaminating signals that are inherently produced as a result of laser ultrasound inspection.