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http://hdl.handle.net/10397/1506
| Title: | Regularized restoration of VQ compressed images with constrained least squares approach | Authors: | Choy, SSO Yue, CN Hong, SW Chan, YH |
Issue Date: | 1997 | Source: | ISCAS '97 : proceedings of 1997 IEEE International Symposium on Circuits and Systems : circuits and systems in the information age : June 9-12, 1997, Hong Kong, p. 1257-1260 | Abstract: | In this paper, an iterative algorithm is proposed to restore VQ-encoded images. This algorithm incorporates adaptivity into simple CLS restoration algorithm by weighting every pixel according to its expected derivation from the original. This algorithm is fully compatible with any VQ codec to improve codec's coding performance. Computer simulations showed that the proposed scheme was superior to other conventional schemes in terms of SNR improvement. Besides, the image quality could also be improved subjectively by reducing the blocking effect. | Keywords: | Adaptive algorithms Computer simulation Image coding Image compression Image quality Iterative methods Least squares approximations Signal to noise ratio Vector quantization |
Publisher: | IEEE | ISBN: | 0-7803-3583-X | Rights: | © 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| Appears in Collections: | Conference Paper |
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| Regularized restaration of VQ compressed images _97.pdf | 329.3 kB | Adobe PDF | View/Open |
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