In this paper, we shall present two efficient codebook-matching schemes with a locally adaptive vector quantizer (LAVQ) and a search-ordering coding vector quantizer (SOCVQ) to be applied in the Vector Quantization (VQ) encoding system. The proposed codebook-matching schemes exploit the correlation property between adjacent image blocks so that the process of codebook matching can be speed up. Simulation results show that the time complexity of the proposed schemes is lower than those of PCA, Multipath TSVQ, and DPTSVQ. Moreover, the image quality of the proposed methods is close to those processed by the other methods.
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In non-destructive testing with radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptance or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represent the real defect as accurately as possible, the choice of the thresholding methods must be made judiciously. In this paper, performance criteria are used to conduct a comparative study of the thresholding methods based on the gray level histogram, the 2D histogram and the locally adaptive approach to weld defect detection in radiographic images.
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