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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jin-tai Shangguan Yan-ling Li Yong-gang Wang Hui-ling Li |
| Copyright Year | 2011 |
| Description | Author affiliation: Dept. of Computer Science and Technology, Changzhi College, Shanxi province, China (Jin-tai Shangguan; Yan-ling Li; Yong-gang Wang; Hui-ling Li) |
| Abstract | Cubic convolution interpolation algorithm is one of the most widely used image interpolation methods. Compared with the linear interpolation, it has a more accurate result, but a lower interpolation speed due to its computational complexity. The cubic convolution algorithm needs sixteen points in two-dimensional image interpolation. The new algorithm proposed in this paper reduces the necessary points to nine by using the correlation among neighboring pixels. Furthermore, the times of multiplication and addition involved in interpolation can be reduced to 53% and 48% respectively of those by original cubic convolution. So the new algorithm achieved lower computational complexity and a higher interpolation speed. |
| Starting Page | 1072 |
| Ending Page | 1075 |
| File Size | 721333 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424493043 |
| e-ISBN | 9781424493067 |
| DOI | 10.1109/CISP.2011.6100267 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-15 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Interpolation Accuracy Convolution correlation among neighboring pixels Signal processing algorithms Image restoration fast algorithm Kernel cubic convolution interpolation interpolation precision |
| Content Type | Text |
| Resource Type | Article |
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