Abstract
This paper presents a novel parallel approach to monochrome image compression. The coding scheme, called lpifs, consists of linear prediction followed by iterated function systems, which are employed instead of the usual quantizers to encode the predictive residuals. This technique has been implemented on the Meiko CS 1 and is easily extended to all distributed-memory MIMD architectures. Experimental tests have shown that lpifs can achieve very low bit-rates with satisfactory subjective and objective quality. For high compression ratios, lpifs can be considered an effective alternative to standard techniques such as jpeg. The high intrinsic parallelism of the proposed scheme yields speedups close to the number of processors.
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Keywords
- Parallel Implementation
- Linear Prediction
- Iterate Function System
- Predictive Code
- High Compression Ratio
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© 1996 Springer-Verlag Berlin Heidelberg
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Vecchia, G.D., Distasi, R., Nappi, M., Vitulano, D. (1996). A parallel implementation of image coding using linear prediction and iterated function systems. In: Bougé, L., Fraigniaud, P., Mignotte, A., Robert, Y. (eds) Euro-Par'96 Parallel Processing. Euro-Par 1996. Lecture Notes in Computer Science, vol 1124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0024696
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DOI: https://doi.org/10.1007/BFb0024696
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