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

Authors:
Ismael Baeza;José-Antonio Verdoy;Rafael-Jacinto Villanueva;Javier Villanueva-Oller
Affiliations:
Instituto de Matemática Multidisciplinar, Edificio 8G piso 2, Universidad Politécnica de Valencia, 46022 Valencia, Spain;Instituto de Matemática Multidisciplinar, Edificio 8G piso 2, Universidad Politécnica de Valencia, 46022 Valencia, Spain;Instituto de Matemática Multidisciplinar, Edificio 8G piso 2, Universidad Politécnica de Valencia, 46022 Valencia, Spain;Ing. Técnica Informática de Sistemas, CES Felipe II, Aranjuez, Madrid, Spain
Venue:
Image and Vision Computing
Year:
2010

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Abstract

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.