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SVD lossy adaptive encoding of 3D digital images for ROI progressive transmission

机译:3D数字图像的SVD有损自适应编码,用于ROI渐进式传输

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In this paper, we propose an algorithm for lossy adaptive encoding of digital three-dimensional (3D) images based on singular value decomposition (SVD). This encoding allows us to design algorithms for progressive transmission and reconstruction of the 3D image, for one or several selected regions of interest (ROI) avoiding redundancy in data transmission. The main characteristic of the proposed algorithms is that the ROIs can be selected during the transmission process and it is not necessary to re-encode the image again to transmit the data corresponding to the selected ROI. An example with a data set of a CT scan consisting of 93 parallel slices where we added an implanted tumor (the ROI in this example) and a comparative with JPEG2000 are given.
机译:在本文中,我们提出了一种基于奇异值分解(SVD)的数字三维(3D)图像有损自适应编码算法。这种编码使我们可以为一个或几个选定的感兴趣区域(ROI)设计用于3D图像的渐进式传输和重建的算法,从而避免数据传输中的冗余。所提出的算法的主要特征是,可以在传输过程中选择ROI,并且不必再次重新编码图像以传输与所选ROI相对应的数据。给出了一个包含93个平行切片的CT扫描数据集的示例,其中添加了植入的肿瘤(在本示例中为ROI),并与JPEG2000作了比较。

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