Transforms for intra prediction residuals based on prediction inaccuracy modeling
In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
|
| Online Access: | http://hdl.handle.net/1721.1/108261 https://orcid.org/0000-0002-5955-4978 https://orcid.org/0000-0002-9170-784X |
| _version_ | 1826202926022918144 |
|---|---|
| author | Cai, Xun Lim, Jae S |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Cai, Xun Lim, Jae S |
| author_sort | Cai, Xun |
| collection | MIT |
| description | In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra prediction is most effective in smooth regions and edges with a particular direction. In the ideal case, edges can be predicted fairly accurately with an accurate prediction direction. In practice, an accurate prediction direction is hard to obtain. Based on the inaccuracy of prediction direction that arises in the design of many practical video coding systems, we can estimate the residual variance and propose a class of transforms based on the estimated variance function. The proposed method is evaluated by the energy compaction property. Experimental results show that with the proposed method, the same amount of energy in directional intra prediction residuals can be preserved with a significantly smaller number of transform coefficients. |
| first_indexed | 2024-09-23T12:27:03Z |
| format | Article |
| id | mit-1721.1/108261 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:27:03Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1082612022-09-28T08:02:58Z Transforms for intra prediction residuals based on prediction inaccuracy modeling Cai, Xun Lim, Jae S Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Research Laboratory of Electronics Lim, Jae Cai, Xun Lim, Jae S In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra prediction is most effective in smooth regions and edges with a particular direction. In the ideal case, edges can be predicted fairly accurately with an accurate prediction direction. In practice, an accurate prediction direction is hard to obtain. Based on the inaccuracy of prediction direction that arises in the design of many practical video coding systems, we can estimate the residual variance and propose a class of transforms based on the estimated variance function. The proposed method is evaluated by the energy compaction property. Experimental results show that with the proposed method, the same amount of energy in directional intra prediction residuals can be preserved with a significantly smaller number of transform coefficients. 2017-04-19T18:10:23Z 2017-04-19T18:10:23Z 2015-12 2015-09 Article http://purl.org/eprint/type/JournalArticle 978-1-4799-8339-1 http://hdl.handle.net/1721.1/108261 Cai, Xun, and Jae S. Lim. “Transforms for Intra Prediction Residuals Based on Prediction Inaccuracy Modeling.” 2015 IEEE International Conference on Image Processing (ICIP), 27-30 September, 2015, Quebec City, Canada, IEEE, 2015. pp. 4401–4405. https://orcid.org/0000-0002-5955-4978 https://orcid.org/0000-0002-9170-784X en_US http://dx.doi.org/10.1109/ICIP.2015.7351638 Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Prof. Lim via Phoebe Ayers |
| spellingShingle | Cai, Xun Lim, Jae S Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title | Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title_full | Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title_fullStr | Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title_full_unstemmed | Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title_short | Transforms for intra prediction residuals based on prediction inaccuracy modeling |
| title_sort | transforms for intra prediction residuals based on prediction inaccuracy modeling |
| url | http://hdl.handle.net/1721.1/108261 https://orcid.org/0000-0002-5955-4978 https://orcid.org/0000-0002-9170-784X |
| work_keys_str_mv | AT caixun transformsforintrapredictionresidualsbasedonpredictioninaccuracymodeling AT limjaes transformsforintrapredictionresidualsbasedonpredictioninaccuracymodeling |