Actas JP2011 - Universidad de La Laguna

Actas XXII Jornadas de Paralelismo (JP2011) , La Laguna, Tenerife, 7-9 septiembre 2011TABLE IIISign compression performance at different bit-rates.Bit-rate S-LTW SPIHT %Gain(bpp) #Significant #Bits #Significant #BitsCoefficients Saved Coefficients SavedBarbara (512x512)1 45740 7936 54657 9482 17.350.5 22331 3648 27535 4499 16.340.25 10484 1520 13460 1951 14.500.125 4343 304 6016 421 7.00Bike (2048x2560)1 855266 115200 1371280 184711 13.470.5 412212 64424 798202 124758 15.630.25 198943 30472 366927 56213 15.320.125 91767 11992 162990 21302 13.07P PSNR (d dB)0.5 S-LTW vs SPIHT0.4LTW vs SPIHTS-LTW vs JPEG20000.3LTW vs JPEG20000.20.100-0.10.5 1 1.5 2-0.2-0.3-0.4-0.5Fig. 2.Bit-rate (bpp)PSNR-Gain for Bike imageis 17.35%. Furthermore, we show an estimation ofthe bit savings for SPIHT encoder.TABLE IVCoding delay (seconds).Bit-rate JPEG SPIHT LTW S-LTW(bpp) 2000 Orig.CODING Barbara (512x512)1 0.080 0.042 0.037 0.0230.5 0.076 0.026 0.022 0.0140.25 0.074 0.018 0.013 0.0090.125 0.073 0.014 0.010 0.006CODING Bike (2048x2560)1 2.623 0.920 0.647 0.4300.5 2.543 0.521 0.381 0.2590.25 2.507 0.323 0.224 0.1620.125 2.518 0.221 0.158 0.117In Figure 2 we show the R/D improvement whencomparing original LTW versus JPEG2000/SPIHTand S-LTW versus JPEG2000/SPIHT. As shown,there is an increase in the PSNR difference betweenSPIHT and the new S-LTW encoder, and regardingJPEG2000, we can see than now S-LTW has a minorloss in PSNR than original LTW.Regarding coding delay, the use of a higher contextmodeling in the arithmetic encoder implies a highercomputational cost. In order to compensate the codingspeed loss, we have changed the arithmetic encoderstage by a fast arithmetic encoder [11]. Asit can be seen in Table IV, S-LTW encoder is 49%faster on average in the coding process than SPIHTencoder and 86% faster on average than JPEG2000.Furthermore, S-LTW encoder is even faster than theoriginal LTW version which does not include the signcoding stage (1.5 times faster on average in the codingprocess).IV. ConclusionsWe have presented a genetic algorithm that is ableto find a good sign predictor of wavelet coefficientsign. So, by encoding the sign prediction result (successor failure) with an arithmetic encoder, the signinformation will be highly compacted in the final bitstream.In order to prove our proposal we have implementedthe sign predictor over the non-embeddedLTW encoder. The new S-LTW proposed encoderhas slightly better R/D performance (up to 0.25 dB),or in terms of bitstream, it is able to reduce the bitstreamsize up to 17% for the same quality level.Regarding coding delay, the new image encoder ison average 2 times as fast as SPIHT in the codingprocess and 1.5 times as fast as original LTW due tothe inclusion of a fast arithmetic encoder.AcknowledgementsThanks to Spanish Ministry of education and Scienceunder grant DPI2007-66796-C03-03 for funding.References[1] ISO/IEC 15444-1, “JPEG2000 image coding system,”2000.[2] J.M. Shapiro, “A fast technique for identifying zerotreesin the EZW algorithm,” Proc. IEEE Int. Conf. Acoust.,Speech, Signal Processing, vol. 3, pp. 1455–1458, 1996.[3] X. Wu, “High-order context modeling and embeddedconditional entropy coding of wavelet coefficients for imagecompression,” in Proc. of 31st Asilomar Conf. onSignals, Systems, and Computers, 1997, pp. 1378–1382.[4] D. Taubman, “High performance scalable image compressionwith EBCOT,” IEEE Transactions on ImageProcessing, vol. 9, no. 7, pp. 1158–1170, July 2000.JP2011-36