Ñæàòèå èçîáðàæåíèé áåç ïîòåðü:
Ñæàòèå ïîëóòîíîâûõ èçîáðàæåíèé
Àíãëèéñêèå ìàòåðèàëû Èñõîäíûå òåêñòû êîìïðåññîðîâ Òåñòîâûå äàííûå Ïîëåçíûå ññûëêè
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Ðóññêèå ìàòåðèàëû |
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| Àâòîðû | Íàçâàíèå | Îïèñàíèå | Ðåéòèíã |
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Àíãëèéñêèå ìàòåðèàëû | |||
| Ekstrand N. | Universal Lossless Source Coding Techniques for Images and Short Data Sequences | Äîêòîðñêàÿ äèññåðòàöèÿ Íèêëàñà Ýêñòðàíäà. Îñíîâíîé óïîð ñäåëàí íà áåçóùåáíîå ñæàòèå ìåäèöèíñêèõ èçîáðàæåíèé. Îñíîâíîé ìåòîä -- context tree weighting (CTW).
Ph.D. thesis, Lund Institute of Technology, Lund University, 2001. PDF.RAR 890 êáàéò |
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| Ekstrand N. | Lossless Compression of Grayscale Images via Context Tree Weighting | In this article we report on a study of how to use the context tree weighting (CTW) algorithm for lossless image compression... Our study shows that this algorithm can successfully be applied to image compression even in its basic form. We also report on possible modifications of the basic CTW algorithm to let it work more efficiently for image data. Our research is momentarily focussed on the compression of medical gray scale images.
Proceedings of IEEE Data Compression Conference, Snowbird, Utah, pp.132-139, April 1-3, 1996. PDF.RAR 83 êáàéò |
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| Motta G., Storer J., Carpentieri B. | Adaptive Linear Prediction Lossless Image Coding | ...Our investigation is directed to determine the effectiveness of an algorithm that uses multiple adaptive linear predictors, locally optimized on a pixel-by-pixel basis...
Proceedings of IEEE Data Compression Conference, Snowbird, Utah, March 29-31, 1999. PDF.RAR 204 êáàéò |
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| Lee W.S. | Edge Adaptive Prediction for Lossless Image Coding | We design an edge adaptive predictor for lossless image coding. The predictor adaptively weights four directional predictor together with an adaptive linear predictor based on information from neighbouring pixels. Although conceptually simple, the performance of the resulting coder is comparable to state of the art image coders when a simple context based coder is used to encode the prediction errors.
Proceedings of IEEE Data Compression Conference, Snowbird, Utah, March 29-31, 1999. PDF.RAR 76 êáàéò |
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| Dawson-Howe K. | Lossless Image Compression using a Simple Prediction Method | This paper describes a new straight-forward technique for lossless image compression, entitled SPM (Simple Prediction Method)... The predictive model used by the method is one in which the current point is predicted as a weighted average of the preceding neighbouring points. The weights for this mask are encoded within the compressed image...
Department of Computer Science,Trinity College, Dublin, Ireland, March 8, 1996. PDF.RAR 226 êáàéò PS.RAR 464 êáàéò |
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| Carpentieri B., Weinberger M., Seroussi G. | Lossless Compression of Continuous-Tone Images | In this paper, we survey some of the recent advances in lossless compression of continuous-tone images. The modeling paradigms underlying the state-of-the-art algorithms, and the principles guiding their design, are discussed in a unified manner. The algorithms are described and
experimentally compared.
Hewlett-Packard Laboratories technical report HPL-2000-163, December 8th, 2000. PDF.RAR 301 êáàéò |
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| Meyer B., Tischer P. | Glicbawls - Grey Level Image Compression By Adaptive Weighted Least Squares. |
Èç ââåäåíèÿ:
What has been largely missing so far is an algorithm that combines the compression
rates of the impractical algorithms with the moderate computational requirements of
the practical ones. In this paper, we present Glicbawls, an algorithm that achieves that
goal for natural images.
Ñòðàíè÷êà ïðîåêòà PDF 274 êáàéò PS.RAR 101 êáàéò |
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| Clunie D. | Lossless Compression of Grayscale Medical Images -- Effectiveness of Traditional and State of the Art Approaches | Âåñüìà íåäóðíîå ñðàâíåíèå ñòåïåíè ñæàòèÿ ðàçëè÷íûõ êîäåêîâ áåçóùåðáíîãî ñæàòèÿ íà áîëüøîì íàáîðå ïîëóòîíîâûõ ìåäèöèíñêèõ èçîáðàæåíèé.
Quintiles Intelligent Imaging, 2000. PDF.RAR 287 êáàéò |
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| Bernd Meyer, Peter Tischer | TMW - a new method for lossless image compression. |
We present a general purpose lossless greyscale image compression method, TMW,
that is based on the use of linear predictors and implicit segmentation. In
order to achieve competitive compression, the compression process is split
into an analysis step and a coding step. In the first step, a set of linear
predictors and other parameters suitable for the image is calculated, which is
included in the compressed file and subsequently used for the coding step...
Other significant features of TMW are the use of a one-parameter probability
distribution, probability calculations based on unquantized prediction values,
blending of multiple probability distributions instead of prediction values,
and implicit image segmentation.
PCS97 1997 Picture Coding Symposium, VDE-Verlag GMBH, Berlin Germany, 533-538, 1997. PDF 343 êáàéò |
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| Fukunaga A., Stechert A. | Evolving Nonlinear Predictive Models for Lossless Image Compression with Genetic Programming | Èñïîëüçîâàíèå íåëèíåéíîé ïðîãíîñòè÷åñêîé ìîäåëè, ïîäãîíÿåìîé ñ ïîìîùüþ ãåíåòè÷åñêîãî ïðîãðàììèðîâàíèÿ, äëÿ áåçóùåðáíîãî ñæàòèÿ èçîáðàæåíèé. Ïîäõîä ëîáîâîé, òîðìîçèò âñå óæàñíî. Ñæàòèå ïîëó÷àåòñÿ íà 5..10 % âûøå, ÷åì äëÿ CALIC.
Jet Propulsion Laboratory, California Institute of Technology, 1998. PDF.RAR 154 êáàéò |
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| Xiaohui Xue, Wen Gao | Prediction Based on Backward Adaptive Recognition of Local Texture Orientation and Poisson Statistical Model for Lossless/Near-Lossless Image Compression. |
This paper is devoted to prediction-based lossless/near-lossless
image compression algorithm. Within this framework, there are
three modules, including prediction model, statistical model and
entropy coding. This paper focuses on the former two, and puts
forward two new methods respectively, they are, prediction
model based on backward adaptive recognition of local texture
orientation (BAROLTO), and Poisson statistical model.
Proc. 1999 IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing. Phoenix, Arizona, 1999. PS.RAR 216 êáàéò |
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| R.Barequet and M.Feder | SICLIC: A Simple Inter-Color Lossless Image Coder. |
Îïèñàíèå ðàñøèðåíèÿ àëãîðèòìà LOCO-I íà èçîáðàæåíèÿ ñ íåñêîëüêèìè öâåòîâûìè ïëîñêîñòÿìè (íàïðèìåð RGB).
Proceedings of IEEE Data Compression Conference, Snowbird, Utah, March 29-31, 1999. PDF.RAR 1283 êáàéò |
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| G.DENG and H.Ye | Lossless image compression using adaptive predictor combination, symbol mapping and context filtering |
Ñîäåðæàíèå ÿñíî èç íàçâàíèÿ (ðåäêèé ñëó÷àé ;-)).
IEEE 1999 International Conference on Image Processing, Kobe, Japan, Oct. 1999. PS.RAR 4024 êáàéò |
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| B.Meyer, P.Tischer | Extending TMW for Near Lossless Compression of Greyscale Images |
TMW: óáèéöà ïðîöåññîðíîãî âðåìåíè. 2-àÿ ñåðèÿ.
Proceedings of IEEE Data Compression Conference, Snowbird, Utah, March 30, 1998. PDF.RAR 239 êáàéò |
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| Jiang, J., Grecos C. | Towards an improvement of prediction accuracy in JPEG-LS |
Îïèñûâàåòñÿ ìîäèôèêàöèÿ MAP(MED) ïðåäèêòîðà äëÿ LOCO-I/JPEG-LS, óâåëè÷åíèÿ
ýôôåêòèâíîñòè íå îáíàðóæåíî ;-). ÈÌÕÎ, áëåñòÿùàÿ äåìîíñòðàöèÿ òîãî, ÷òî
áåññìûñëåííî óëó÷øàòü îäíó ÷àñòü êîäåêà áåç ó÷åòà îñòàëüíûõ.
Optical Engineering, SPIE, Vol 41, No 2, 2002, pp 273-541 PDF.RAR 433 êáàéò |
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| M. Ciavarella and A. Moffat | Lossless Image Compression Using Pixel Reordering |
Îïèñûâàåòñÿ àíàëîã ïðåîáðàçîâàíèÿ BWT äëÿ ïîëóòîíîâûõ èçîáðàæåíèé,
ïðåäëàãàåòñÿ íîâûé ñïîñîá îáõîäà ïèêñåëîâ èçîáðàæåíèÿ. Ïîëåçíî ïî÷èòàòü äëÿ îáùåãî ðàçâèòèÿ.
Proceedings of the Twenty-Seventh Australasian Computer Science Conference Vol 26, 2004. PDF.RAR 80 êáàéò |
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| Ichiro Matsuda, Nau Ozaki, Yuji Umezu and Susumu Itoh | Lossless Coding Using Variable Block-size Adaptive Prediction Optimized For Each Image |
Îïèñûâàåòñÿ óëó÷øåíèå ìåòîäà MRP ñ ïîìîùüþ àäàïòèâíîãî âûáîðà ðàçìåðîâ
áëîêîâ íà êîòîðûå ðàçáèòî èçîáðàæåíèå. Ê ñîæàëåíèþ, èñõîäíàÿ ñòàòüÿ î MRP
íàïèñàíà íà ÿïîíñêîì è íåäîñòóïíà.
Proceedings of 13th European Signal Processing Conference (EUSIPCO 2005), Sep. 2005. PDF.RAR 179 êáàéò |
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| Ichiro Matsuda, Tomokazu Kaneko, Akira Minezawa and Susumu Itoh | Lossless Coding of Color Images using Block-Adaptive Inter-Color Prediction |
Ïðèìåíåíèå ìåòîäà MRP äëÿ ñæàòèÿ öâåòíûõ èçîáðàæåíèé. Âñå äîñòàòî÷íî îæèäàåìî.
IEEE International Conference on Image Processing (ICIP), 2007. PDF.RAR 108 êáàéò |
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| Feng-Yang Hsieh and Kuo-Chin Fan | A High Performance Lossless Image Coder |
Îïèñûâàåòñÿ äîáàâëåíèå ê ìåòîäó MRP ïðåäèêòîðîâ MED, GAP è MMSE. Îñîáî áîëüøîãî âûèãðûøà íå âèäàòü.
IPPR Conf. on Computer Vision & Graphic Image Processing 2005. PDF.RAR 923 êáàéò |
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| Hua Ye, Guang Deng and John C. Devlin | A Weighted Least Squares Method For Adaptive Prediction in Lossless Image Compression |
Ñæàòèå ñ ïîìîùüþ ìåòîäà íàèìåíüøèõ êâàäðàòîâ, åùå îäèí ïðåòåíäåíò íà ìàêñèìàëüíîå ñæàòèå.
Ïðèìå÷àòåëüíî, ÷òî ïðèíöèïèàëüíî ðàçëè÷íûå ïîäõîäû äàþò ðåçóëüòàòû, ðàçëè÷àþùèåñÿ â ïðåäåëàõ 1%. Áëèçîê-áëèçîê ïðåäåë ñæàòèÿ!
23rd Picture Coding Symposium (Saint-Malo, France), 2003. PDF.RAR 40 êáàéò |
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Èñõîäíûå òåêñòû êîìïðåññîðîâ | |||
| University of British Columbia | Ðåàëèçàöèÿ àëãîðèòìà LOCO/JPEG-LS |
Ðåàëèçàöèÿ îñíîâàíà íà îðèãèíàëüíîì êîäå HP.
ßçûê: C. Ñòðàíè÷êà ïðîåêòà êîäåê 812 êáàéò |
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| Cheng Jiun Yuan | CALIC implementation |
(Ñòóäåí÷åñêàÿ) ðåàëèçàöèÿ àëãîðèòìà CALIC.
ßçûê: C++. Ñòðàíè÷êà ïðîåêòà êîäåê 29 êáàéò |
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| Kongji Huang and Brian Smith | Lossless JPEG Codec |
Ðåàëèçàöèÿ ñòàðîãî àëãîðèòìà lossless JPEG, ïî-ìîåìó ïðåäñòàâëÿåò èíòåðåñ òîëüêî äëÿ èñòîðèêîâ.
ßçûê: C. ftp-àäðåñ Version 1.0 186 êáàéò |
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Òåñòîâûå äàííûå | |||
| Ñàéò | Êîììåíòàðèé | ||
| "Ñòàðûé" òåñòîâûé íàáîð JPEG + LENA image | Íàèáîëåå ÷àñòî èñïîëüçóåìûé â ëèòåðàòóðå íàáîð. | ||
| Waterloo BragZone | Íàáîð îðèåíòèðîâàí íà ñðàâíåíèå lossy-êîäåêîâ, íî è äëÿ áåñïîòåðüíûõ òîæå ñîéäåò. | ||
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Ïîëåçíûå ññûëêè | |||
| Ñòðàíè÷êà ïðîåêòà MRP | Íàèáîëåå ñèëüíûé áåñïîòåðüíûé êîäåð â íàñòîÿùåå âðåìÿ | ||
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