Abstract: The present disclosure is related to techniques for the inspection of joints and repairs in pipelines. In this scenario, the a method is provided for the inspection of joints in composite pipes and of composite repairs in metallic pipelines, comprising the steps of (i) emitting a series of acoustic wave pulses, at different frequencies, from a collar of acoustic transducers positioned at a predetermined distance from a joint or repair to be inspected, (ii) recording, in a time interval subsequent to the emission, echoes of wave displacements to the repair or joint in each of the transducers in the form of an A-Scan, and (iii) generating a flattened C-Scan image, through a CSM, for each frequency of pulse emission from the collar of acoustic transducers. The disclosure further provides a system for inspection of joints in composite pipes and of composite repairs in metallic pipelines associated with the provided method.

Abstract: This invention relates to a method for de-noising digital radiographic images based upon a wavelet-domain Hidden Markov Tree (HMT) model. The method uses the Anscombe's transformation to adjust the original image to a Gaussian noise model. The image is then decomposed in different sub-bands of frequency and orientation responses using a dual-tree complex wavelet transform, and the HMT is used to model the marginal distribution of the wavelet coefficients. Two different methods were used to denoise the wavelet coefficients. Finally, the modified wavelet coefficients are transformed back into the original domain to get the de-noised image.