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- W2007106458 abstract "This paper presents a promising super-resolution (SR) approach using maximum a posteriori (MAP) estimation. We consider the high resolution (HR) estimation as a Markov Random Field (MRF), using a transformed gradient field prior to repair the image fuzzy problem caused by MRF. An improved Normalized Convolution method is proposed to obtain a first good estimation. We build a reasonable energy function and minimize the posterior energy by gradient descent algorithm. Experimental results on realistic image sequence and comparisons with several other SR techniques show that our approach gives the best results both qualitative and quantitative." @default.
- W2007106458 created "2016-06-24" @default.
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- W2007106458 date "2013-05-27" @default.
- W2007106458 modified "2023-10-18" @default.
- W2007106458 title "Image Super-Resolution Reconstruction Using Map Estimation" @default.
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- W2007106458 doi "https://doi.org/10.7148/2013-0838" @default.
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