Name
Abstract | ||
|---|---|---|
ABSTRACT This paper presents a context-based predictive coding method for lossless compression of video. For this method, we pro- pose a model to estimate level of activity in the prediction context of a pixel. This is measured,in terms of slope and the same is optimally classified to results in a small num- ber of slope bins. After finding the slope bins, we propose a LS based method to find switched predictors to be associated with the various bins. The set of the predictors are found on a frame-by-frame basis and when it is incorporated in CALIC frame work, the proposed method results in, on an average, a better compression performance than that is obtained using recently published methods - LOPT and M-CALIC. The pro- posed codec has higher coding complexity but much,lower decoding complexity, which is necessary for real-time video decoding. The proposed method of coding, however, has much lower complexity as compared to the LOPT method, which has same order of high coding and decoding complex- ity. Index Terms— GAP, Slope Bins, Gradient, LS-based pre- |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICIP.2007.4379523 | Image Processing, 2007. ICIP 2007. IEEE International Conference |
Keywords | Field | DocType |
adaptive decoding,data compression,decoding,gradient methods,least mean squares methods,prediction theory,real-time systems,video codecs,video coding,CALIC frame work,context-based predictive coding,gradient method,least-squares method,real-time video decoding,slope bins,switched adaptive predictors,video codec,video compression,GAP,Gradient,LS-based predictor,Slope Bins | Least squares,Pattern recognition,Computer science,Coding (social sciences),Pixel,Artificial intelligence,Decoding methods,Data compression,Codec,Context-adaptive binary arithmetic coding,Lossless compression | Conference |
Volume | ISSN | ISBN |
6 | 1522-4880 E-ISBN : 978-1-4244-1437-6 | 978-1-4244-1437-6 |
Citations | PageRank | References |
2 | 0.45 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anil Kumar Tiwari | 1 | 2 | 0.45 |
| Ratnam V. Raja Kumar | 2 | 11 | 2.41 |