Title :
Rank order polynomial decomposition for image compression
Author :
Egger, Olivier ; Grüter, Reto ; Vesin, Jean-Marc ; Kunt, Murat
Author_Institution :
Signal Process. Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland
Abstract :
A novel decomposition scheme for image compression is presented. It is capable of applying any nonlinear model to compress images in a lossless way. Here, a very efficient polynomial model that considers spatial information as well as order statistic information is introduced. This new rank order polynomial decomposition (ROPD) that allows also for a progressive bitstream is applied to various images of different nature and compared to the morphological subband decomposition (MSD) and to the best prediction mode for lossless compression of the international standard, JPEG. For all compressed images, ROPD provides better compression results than MSD and clearly outperforms the lossless mode of JPEG
Keywords :
biomedical ultrasonics; data compression; image coding; image reconstruction; image representation; medical image processing; polynomials; statistical analysis; JPEG; image compression; international standard; lossless compression; lossless representation; medical applications; morphological subband decomposition; nonlinear model; order statistics; polynomial model; progressive bitstream; rank order polynomial decomposition; reconstructed image; spatial information; ultrasound images; Image coding; Laboratories; Pixel; Polynomials; Prediction methods; Predictive models; Statistics; Testing; Transform coding; Visual communication;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.678065
