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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Memon, N. Moayeri, N. |
| Copyright Year | 1997 |
| Description | Author affiliation: Dept. of Comput. Sci., Northern Illinois Univ., DeKalb, IL, USA (Memon, N.) |
| Abstract | This paper presents a new criterion for near-lossless image compression and compares it with the more familiar maximum pixel error criterion in terms of compression performance and coded image subjective quality. In this new framework we compress an image in such a way that at each pixel the total error between the original and the coded images over a W/spl times/W window around the pixel does not exceed /spl epsiv/ in magnitude. The new criterion's main advantage is that it preserves image brightness and color. The compression scheme used in this work is similar to a trellis-searched scheme proposed by Ke and Marcellin (1995) in that our scheme is also a predictive, context-based scheme. However, the search for all optimal paths, representing a set of reconstruction values for an image row that satisfies the error criterion and yields the minimum bit rate, has to be done in a planar directed graph instead of a trellis. We show that this framework is also applicable to a joint image filtering and compression scenario. We present simulation results showing the performance of the new error criterion and compare it with the maximum pixel error criterion. |
| Starting Page | 662 |
| Ending Page | 665 |
| File Size | 468508 |
| Page Count | 4 |
| File Format | |
| ISBN | 0818681837 |
| DOI | 10.1109/ICIP.1997.632208 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1997-10-26 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image coding Pixel Image reconstruction ISO standards Computer errors Brightness Transform coding IEC standards Computer science Laboratories |
| Content Type | Text |
| Resource Type | Article |
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