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		<isbn>85-244-0103-6</isbn>
		<citationkey>DarsaCost:1996:MuReRe</citationkey>
		<title>Multiresolution representation and reconstruction of adaptively sampled images</title>
		<format>Impresso, On-line.</format>
		<year>1996</year>
		<numberoffiles>1</numberoffiles>
		<size>256 KiB</size>
		<author>Darsa, Lucia,</author>
		<author>Costa, Bruno,</author>
		<editor>Velho, Luiz,</editor>
		<editor>Albuquerque, Arnaldo de,</editor>
		<editor>Lotufo, Roberto A.,</editor>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 9 (SIBGRAPI)</conferencename>
		<conferencelocation>Caxambu</conferencelocation>
		<date>29 out. - 1 nov. 1996</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<pages>321-328</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigo</tertiarytype>
		<organization>SBC - Sociedade Brasileira de Computação; UFMG - Universidade Federal de Minas Gerais</organization>
		<transferableflag>1</transferableflag>
		<abstract>We present a method for sampling, structuring and reconstructing progressively refined images effectively. This has direct applications to progressive refinement of the result of slow renderers, such as ray tracers, and to the progressive transmission of images on slow media, as in world wide web browsers. Sampling images adaptively with respect to frequency at the back end provides a more compact representation. These samples are then structured at the front end using Voronoi or Delaunay tesselations, and reconstructed with C^0 continuity taking advantage of standard 3D acceleration hardware. The structuring scheme is extended to handle multiresolution images, with optional antialiasing, allowing the representation of an arbitrary level of detail without penalizing the reconstruction.</abstract>
		<type>Processamento de Imagens</type>
		<language>en</language>
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