IEEE Trans Image Process - Multiscale semilocal interpolation with antialiasing.

Tópicos

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Resumo

Aliasing is a common artifact in low-resolution (LR) images generated by a downsampling process. Recovering the original high-resolution image from its LR counterpart while at the same time removing the aliasing artifacts is a challenging image interpolation problem. Since a natural image normally contains redundant similar patches, the values of missing pixels can be available at texture-relevant LR pixels. Based on this, we propose an iterative multiscale semilocal interpolation method that can effectively address the aliasing problem. The proposed method estimates each missing pixel from a set of texture-relevant semilocal LR pixels with the texture similarity iteratively measured from a sequence of patches of varying sizes. Specifically, in each iteration, top texture-relevant LR pixels are used to construct a data fidelity term in a maximum a posteriori estimation, and a bilateral total variation is used as the regularization term. Experimental results compared with existing interpolation methods demonstrate that our method can not only substantially alleviate the aliasing problem but also produce better results across a wide range of scenes both in terms of quantitative evaluation and subjective visual quality.

Resumo Limpo

alias common artifact lowresolut lr imag generat downsampl process recov origin highresolut imag lr counterpart time remov alias artifact challeng imag interpol problem sinc natur imag normal contain redund similar patch valu miss pixel can avail texturerelev lr pixel base propos iter multiscal semiloc interpol method can effect address alias problem propos method estim miss pixel set texturerelev semiloc lr pixel textur similar iter measur sequenc patch vari size specif iter top texturerelev lr pixel use construct data fidel term maximum posteriori estim bilater total variat use regular term experiment result compar exist interpol method demonstr method can substanti allevi alias problem also produc better result across wide rang scene term quantit evalu subject visual qualiti

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