Many image encoders exist that reduce the amount of information that needs to be transmitted or stored on disk. Reduction of information reduces the transmission rate but compromises i~age quality. The encoders that have the best compression ratios often lose image quality by distorting the high frequency portions of the image. Other encoders have slow algorithms that will not work in real time. Encoders that use quantizers often exhibit a gray scale contouring effect due to insufficient quantizer levels. This paper presents a fast encoding algorithm that reduces the number of quantizer levels without introducing an error large enough to cause gray scale contouring. The new algorithm uses entropy to determine the most advantageous difference mapping technique and the number of bits per pixel used to encode the image. The double Difference values are reduced in magnitude such that an eight level power series quantizer can be used without introducing an error large enough to cause gray scale contouring. The one dimensional application of the algorithm results in 3.0 bits per pixel with a RMS error of 4.2 gray scale values. Applied two dimensionally, the algorithm reduces the image to 1.5 bits per pixel with a RMS error of 6.7 gray scale values.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:rtd-5047 |
| Date | 01 January 1990 |
| Creators | Murphy, Gregory Paul |
| Publisher | University of Central Florida |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Retrospective Theses and Dissertations |
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