Abstract
This paper addresses the novel idea of whether it is possible to perform spatial matching of compressed images. What are the fundamental problems and limitations of limiting the knowledge to that of the compressed image? We present an algorithm which matches transform block encoded images, without performing the decoding stage. The theoretical 2D image matching model is developed and applied to the discrete Karhunen-Loeve transform and the discrete cosine transform. In addition, we discuss the tradeoffs in using our algorithm for matching compressed images. As a validation step, we apply our algorithm to a video sequence and discuss the results for 2D matching and 3D reconstruction.
| Original language | English (US) |
|---|---|
| Article number | 413665 |
| Pages (from-to) | 720-724 |
| Number of pages | 5 |
| Journal | Proceedings - International Conference on Image Processing, ICIP |
| Volume | 2 |
| DOIs | |
| State | Published - Jan 1 1994 |
| Event | Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994 |
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ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing
Cite this
Image compression and matching. / Lew, M. S.; Huang, T. S.
In: Proceedings - International Conference on Image Processing, ICIP, Vol. 2, 413665, 01.01.1994, p. 720-724.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Image compression and matching
AU - Lew, M. S.
AU - Huang, T. S.
PY - 1994/1/1
Y1 - 1994/1/1
N2 - This paper addresses the novel idea of whether it is possible to perform spatial matching of compressed images. What are the fundamental problems and limitations of limiting the knowledge to that of the compressed image? We present an algorithm which matches transform block encoded images, without performing the decoding stage. The theoretical 2D image matching model is developed and applied to the discrete Karhunen-Loeve transform and the discrete cosine transform. In addition, we discuss the tradeoffs in using our algorithm for matching compressed images. As a validation step, we apply our algorithm to a video sequence and discuss the results for 2D matching and 3D reconstruction.
AB - This paper addresses the novel idea of whether it is possible to perform spatial matching of compressed images. What are the fundamental problems and limitations of limiting the knowledge to that of the compressed image? We present an algorithm which matches transform block encoded images, without performing the decoding stage. The theoretical 2D image matching model is developed and applied to the discrete Karhunen-Loeve transform and the discrete cosine transform. In addition, we discuss the tradeoffs in using our algorithm for matching compressed images. As a validation step, we apply our algorithm to a video sequence and discuss the results for 2D matching and 3D reconstruction.
UR - http://www.scopus.com/inward/record.url?scp=84999808929&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84999808929&partnerID=8YFLogxK
U2 - 10.1109/ICIP.1994.413665
DO - 10.1109/ICIP.1994.413665
M3 - Conference article
AN - SCOPUS:84999808929
VL - 2
SP - 720
EP - 724
JO - Proceedings - International Conference on Image Processing, ICIP
JF - Proceedings - International Conference on Image Processing, ICIP
SN - 1522-4880
M1 - 413665
ER -