Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images. Park, S. C., Kang, M. G., Segall, C. A., Katsaggelos, A. K. A., Sung Cheol, P., Moon Gi, K., Segall, C. A., Aggelos, K K., Sung Cheal, P., Moon Gi, K., Segall, C. A., Aggelos, K K., Sung Cheol Park, Moon Gi Kang, Segall, C. A., & Katsaggelos, A. K. A. In Proceedings. International Conference on Image Processing, volume 2, pages II—-II, 2002. IEEE, IEEE. ![Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered in this paper. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process. The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced not only to reflect the relative amount of registration error in each low-resolution image but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.
@inproceedings{SungCheolPark2002,
abstract = {The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered in this paper. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process. The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced not only to reflect the relative amount of registration error in each low-resolution image but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.},
author = {Park, Sung Cheol and Kang, Moon Gi and Segall, C.A. Andrew and Katsaggelos, Aggelos K. A.K. and {Sung Cheol}, Park and {Moon Gi}, Kang and Segall, C.A. Andrew and Aggelos, K Katsaggelos and {Sung Cheal}, Park and {Moon Gi}, Kang and Segall, C.A. Andrew and Aggelos, K Katsaggelos and {Sung Cheol Park} and {Moon Gi Kang} and Segall, C.A. Andrew and Katsaggelos, Aggelos K. A.K.},
booktitle = {Proceedings. International Conference on Image Processing},
doi = {10.1109/ICIP.2002.1040087},
isbn = {0-7803-7622-6},
issn = {10577149},
keywords = {DCT-based compression,High-resolution image reconstruction,Quantization noise,Regularization},
number = {4},
organization = {IEEE},
pages = {II----II},
pmid = {15376591},
publisher = {IEEE},
title = {{Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images}},
url = {http://ieeexplore.ieee.org/document/1040087/},
volume = {2},
year = {2002}
}
Downloads: 0
{"_id":"SW6Fkdj5SYuxb6BF5","bibbaseid":"park-kang-segall-katsaggelos-sungcheol-moongi-segall-aggelos-etal-spatiallyadaptivehighresolutionimagereconstructionoflowresolutiondctbasedcompressedimages-2002","author_short":["Park, S. C.","Kang, M. G.","Segall, C. A.","Katsaggelos, A. K. A.","Sung Cheol, P.","Moon Gi, K.","Segall, C. A.","Aggelos, K K.","Sung Cheal, P.","Moon Gi, K.","Segall, C. A.","Aggelos, K K.","Sung Cheol Park","Moon Gi Kang","Segall, C. A.","Katsaggelos, A. K. A."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","abstract":"The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered in this paper. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process. The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced not only to reflect the relative amount of registration error in each low-resolution image but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.","author":[{"propositions":[],"lastnames":["Park"],"firstnames":["Sung","Cheol"],"suffixes":[]},{"propositions":[],"lastnames":["Kang"],"firstnames":["Moon","Gi"],"suffixes":[]},{"propositions":[],"lastnames":["Segall"],"firstnames":["C.A.","Andrew"],"suffixes":[]},{"propositions":[],"lastnames":["Katsaggelos"],"firstnames":["Aggelos","K.","A.K."],"suffixes":[]},{"propositions":[],"lastnames":["Sung Cheol"],"firstnames":["Park"],"suffixes":[]},{"propositions":[],"lastnames":["Moon Gi"],"firstnames":["Kang"],"suffixes":[]},{"propositions":[],"lastnames":["Segall"],"firstnames":["C.A.","Andrew"],"suffixes":[]},{"propositions":[],"lastnames":["Aggelos"],"firstnames":["K","Katsaggelos"],"suffixes":[]},{"propositions":[],"lastnames":["Sung Cheal"],"firstnames":["Park"],"suffixes":[]},{"propositions":[],"lastnames":["Moon Gi"],"firstnames":["Kang"],"suffixes":[]},{"propositions":[],"lastnames":["Segall"],"firstnames":["C.A.","Andrew"],"suffixes":[]},{"propositions":[],"lastnames":["Aggelos"],"firstnames":["K","Katsaggelos"],"suffixes":[]},{"firstnames":[],"propositions":[],"lastnames":["Sung Cheol Park"],"suffixes":[]},{"firstnames":[],"propositions":[],"lastnames":["Moon Gi Kang"],"suffixes":[]},{"propositions":[],"lastnames":["Segall"],"firstnames":["C.A.","Andrew"],"suffixes":[]},{"propositions":[],"lastnames":["Katsaggelos"],"firstnames":["Aggelos","K.","A.K."],"suffixes":[]}],"booktitle":"Proceedings. International Conference on Image Processing","doi":"10.1109/ICIP.2002.1040087","isbn":"0-7803-7622-6","issn":"10577149","keywords":"DCT-based compression,High-resolution image reconstruction,Quantization noise,Regularization","number":"4","organization":"IEEE","pages":"II—-II","pmid":"15376591","publisher":"IEEE","title":"Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images","url":"http://ieeexplore.ieee.org/document/1040087/","volume":"2","year":"2002","bibtex":"@inproceedings{SungCheolPark2002,\nabstract = {The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered in this paper. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process. The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced not only to reflect the relative amount of registration error in each low-resolution image but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.},\nauthor = {Park, Sung Cheol and Kang, Moon Gi and Segall, C.A. Andrew and Katsaggelos, Aggelos K. A.K. and {Sung Cheol}, Park and {Moon Gi}, Kang and Segall, C.A. Andrew and Aggelos, K Katsaggelos and {Sung Cheal}, Park and {Moon Gi}, Kang and Segall, C.A. Andrew and Aggelos, K Katsaggelos and {Sung Cheol Park} and {Moon Gi Kang} and Segall, C.A. Andrew and Katsaggelos, Aggelos K. A.K.},\nbooktitle = {Proceedings. International Conference on Image Processing},\ndoi = {10.1109/ICIP.2002.1040087},\nisbn = {0-7803-7622-6},\nissn = {10577149},\nkeywords = {DCT-based compression,High-resolution image reconstruction,Quantization noise,Regularization},\nnumber = {4},\norganization = {IEEE},\npages = {II----II},\npmid = {15376591},\npublisher = {IEEE},\ntitle = {{Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images}},\nurl = {http://ieeexplore.ieee.org/document/1040087/},\nvolume = {2},\nyear = {2002}\n}\n","author_short":["Park, S. C.","Kang, M. G.","Segall, C. A.","Katsaggelos, A. K. A.","Sung Cheol, P.","Moon Gi, K.","Segall, C. A.","Aggelos, K K.","Sung Cheal, P.","Moon Gi, K.","Segall, C. A.","Aggelos, K K.","Sung Cheol Park","Moon Gi Kang","Segall, C. A.","Katsaggelos, A. K. A."],"key":"SungCheolPark2002","id":"SungCheolPark2002","bibbaseid":"park-kang-segall-katsaggelos-sungcheol-moongi-segall-aggelos-etal-spatiallyadaptivehighresolutionimagereconstructionoflowresolutiondctbasedcompressedimages-2002","role":"author","urls":{"Paper":"http://ieeexplore.ieee.org/document/1040087/"},"keyword":["DCT-based compression","High-resolution image reconstruction","Quantization noise","Regularization"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://sites.northwestern.edu/ivpl/files/2023/06/IVPL_Updated_publications-1.bib","dataSources":["XasdXLL99y5rygCmq","3gkSihZQRfAD2KBo3","t5XMbyZbtPBo4wBGS","bEpHM2CtrwW2qE8FP","teJzFLHexaz5AQW5z"],"keywords":["dct-based compression","high-resolution image reconstruction","quantization noise","regularization"],"search_terms":["spatially","adaptive","high","resolution","image","reconstruction","low","resolution","dct","based","compressed","images","park","kang","segall","katsaggelos","sung cheol","moon gi","segall","aggelos","sung cheal","moon gi","segall","aggelos","sung cheol park","moon gi kang","segall","katsaggelos"],"title":"Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images","year":2002}