IEEE Trans Image Process - Colorization-based compression using optimization.

Tópicos

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Resumo

In this paper, we formulate the colorization-based coding problem into an optimization problem, i.e., an L1 minimization problem. In colorization-based coding, the encoder chooses a few representative pixels (RP) for which the chrominance values and the positions are sent to the decoder, whereas in the decoder, the chrominance values for all the pixels are reconstructed by colorization methods. The main issue in colorization-based coding is how to extract the RP well therefore the compression rate and the quality of the reconstructed color image becomes good. By formulating the colorization-based coding into an L1 minimization problem, it is guaranteed that, given the colorization matrix, the chosen set of RP becomes the optimal set in the sense that it minimizes the error between the original and the reconstructed color image. In other words, for a fixed error value and a given colorization matrix, the chosen set of RP is the smallest set possible. We also propose a method to construct the colorization matrix that colorizes the image in a multiscale manner. This, combined with the proposed RP extraction method, allows us to choose a very small set of RP. It is shown experimentally that the proposed method outperforms conventional colorization-based coding methods as well as the JPEG standard and is comparable with the JPEG2000 compression standard, both in terms of the compression rate and the quality of the reconstructed color image.

Resumo Limpo

paper formul colorizationbas code problem optim problem ie l minim problem colorizationbas code encod choos repres pixel rp chromin valu posit sent decod wherea decod chromin valu pixel reconstruct color method main issu colorizationbas code extract rp well therefor compress rate qualiti reconstruct color imag becom good formul colorizationbas code l minim problem guarante given color matrix chosen set rp becom optim set sens minim error origin reconstruct color imag word fix error valu given color matrix chosen set rp smallest set possibl also propos method construct color matrix color imag multiscal manner combin propos rp extract method allow us choos small set rp shown experiment propos method outperform convent colorizationbas code method well jpeg standard compar jpeg compress standard term compress rate qualiti reconstruct color imag

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