IEEE Trans Image Process - A flexible content-adaptive mesh-generation strategy for image representation.

Tópicos

{ imag(1947) propos(1133) code(1026) }
{ method(2212) result(1239) propos(1039) }
{ can(774) often(719) complex(702) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ import(1318) role(1303) understand(862) }
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{ concept(1167) ontolog(924) domain(897) }
{ imag(2830) propos(1344) filter(1198) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Based on the greedy-point removal (GPR) scheme of Demaret and Iske, a simple yet highly effective framework for constructing triangle-mesh representations of images, called GPRFS, is proposed. By using this framework and ideas from the error diffusion (ED) scheme (for mesh-generation) of Yang et al., a highly effective mesh-generation method, called GPRFS-ED, is derived and presented. Since the ED scheme plays a crucial role in our work, factors affecting the performance of this scheme are also studied in detail. Through experimental results, our GPRFS-ED method is shown to be capable of generating meshes of quality comparable to, and in many cases better than, the state-of-the-art GPR scheme, while requiring substantially less computation and memory. Furthermore, with our GPRFS-ED method, one can easily trade off between mesh quality and computational/memory complexity. A reduced-complexity version of the GPRFS-ED method (called GPRFS-MED) is also introduced to further demonstrate the computational/memory-complexity scalability of our GPRFS-ED method.

Resumo Limpo

base greedypoint remov gpr scheme demaret isk simpl yet high effect framework construct trianglemesh represent imag call gprfs propos use framework idea error diffus ed scheme meshgener yang et al high effect meshgener method call gprfsed deriv present sinc ed scheme play crucial role work factor affect perform scheme also studi detail experiment result gprfsed method shown capabl generat mesh qualiti compar mani case better stateoftheart gpr scheme requir substanti less comput memori furthermor gprfsed method one can easili trade mesh qualiti computationalmemori complex reducedcomplex version gprfsed method call gprfsmed also introduc demonstr computationalmemorycomplex scalabl gprfsed method

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