Efficient colour image compression using fusion approach

References

• Jiang, G., Wong, C., Lin, S., Rahman, M., Ren, T., Kwok, N., Shi, H., Yu, Y.-H. and Wu, T. Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach. J. Mod. Opt., 2015, 62/7, 536–547. doi: 10.1080/09500340.2014.991358
   Web of Science ®Google Scholar
• Cao, G. and Jin, Y. Automatic detection of main road network in dense urban area using microwave sar images. Imaging Sci. J., 2007, 55/4, 215–222. doi: 10.1179/174313107X168981
   Web of Science ®Google Scholar
• Tu, T.-M., Su, S.-C., Shyu, H.-C. and Huang, P. S. A new look at IHS-like image fusion methods. Inf. Fusion, 2001, 2/3, 177–186. doi: 10.1016/S1566-2535(01)00036-7
   Google Scholar
• Tu, T.-M., Huang, P. S., Hung, C.-L. and Chang, C.-P. A fast intensity–hue–saturation fusion technique with spectral adjustment for IKONOS imagery. Geosci. Remote Sens. Lett., 2004, 1/4, 309–312. doi: 10.1109/LGRS.2004.834804
   Web of Science ®Google Scholar
• Rahmani, S., Strait, M., Merkurjev, D., Moeller, M. and Wittman, T. An adaptive IHS pan-sharpening method. Geosci. Remote Sens. Lett., 2010, 7/4, 746–750. doi: 10.1109/LGRS.2010.2046715
   Web of Science ®Google Scholar
• Burt, P. J. and Adelson, E. H. The Laplacian pyramid as a compact image code. IEEE Trans. Commun., 1983, 31/4, 532–540. doi: 10.1109/TCOM.1983.1095851
   Web of Science ®Google Scholar
• Toet, A. A morphological pyramidal image decomposition. Pattern Recogn. Lett., 1989, 9, 255–261. doi: 10.1016/0167-8655(89)90004-4
   Web of Science ®Google Scholar
• Zhou, J., Civco, D. and Silander, J. A wavelet transform method to merge landsat TM and SPOT panchromatic data. Int. J. Remote Sens., 1998, 19/4, 743–757. doi: 10.1080/014311698215973
   Web of Science ®Google Scholar
• Do, M. N. and Vetterli, M. The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans. Image Process., 2005, 14/12, 2091–2106. doi: 10.1109/TIP.2005.859376
   PubMed Web of Science ®Google Scholar
• Candes, E., Demanet, L., Donoho, D. and Ying, L. Fast discrete curvelet transforms. Multiscale Model. Simul., 2006, 5/3, 861–899. doi: 10.1137/05064182X
   Web of Science ®Google Scholar
• González-Audícana, M., Saleta, J. L., Catalán, R. G. and García, R. Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition. IEEE Trans. Geosci. Remote Sens., 2004, 42/6, 1291–1299. doi: 10.1109/TGRS.2004.825593
   Web of Science ®Google Scholar
• Zhou, J., Cunha, A. L. and Do, M. N. Nonsubsampled contourlet transform: construction and application in enhancement. IEEE International Conference on Image Processing, 2005, pp. 1–469.
   Google Scholar
• Ehlers, M. Spectral characteristics preserving image fusion based on fourier domain filtering. ‘Remote sensing’, International Society for Optics and Photonics, 2004, pp. 1–13.
   Google Scholar
• Zhang, Y. Understanding image fusion. Photogramm. Eng. Remote Sens., 2004, 70/6, 657–661.
   Web of Science ®Google Scholar
• Xiao, G., Jing, Z. and Wang, S. Optimal colour image fusion approach based on fuzzy integrals. Imaging Sci. J., 2007, 55/4, 189–196. doi: 10.1179/174313106X156309
   Web of Science ®Google Scholar
• Saeedi, J. and Faez, K. A new pan-sharpening method using multiobjective particle swarm optimization and the shiftable contourlet transform. ISPRS J. Photogramm. Remote Sens., 2011, 66/3, 365–381. doi: 10.1016/j.isprsjprs.2011.01.006
   Web of Science ®Google Scholar
• Rahman, M., Lin, S., Wong, C., Jiang, G. and Kwok, N. Multisensor multichannel image fusion based on fuzzy. 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2014, pp. 135–140.
   Google Scholar
• Shi, A., Huang, C., Huang, F. and Xu, L. Fusion of multispectral and panchromatic images using fuzzy integral based on fast intensity–hue–saturation transform. 33rd Annual Conference of the IEEE Industrial Electronics Society, 2007, pp. 2414–2418.
   Google Scholar
• Yang, F. and Wei, H. Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules. Infrared Phys. Technol., 2013, 60, 235–243. doi: 10.1016/j.infrared.2013.05.008
   Web of Science ®Google Scholar
• Erickson, B. J. Irreversible compression of medical images. J. Digital Imag., 2002, 15, 5–14. doi: 10.1007/s10278-002-0001-z
   PubMed Web of Science ®Google Scholar
• Reid, M., Millar, R. J. and Black, N. D. Second-generation image coding: an overview. ACM Comput. Surv., 1997, 29, 3–29. doi: 10.1145/248621.248622
   Web of Science ®Google Scholar
• Wang, C.-L., Wu, S., Chan, Y. and Chang, R. Quadtree and statistical model-based lossless binary image compression method. Imaging Sci. J., 2005, 53/2, 95–103. doi: 10.1179/136821905X43927
   Web of Science ®Google Scholar
• Natarajan, S., Ramadass, N. and Rao, R. Y. State-based dynamic multi-alphabet arithmetic coding for image compression. Imaging Sci. J., 2009, 57/1, 30–36. doi: 10.1179/174313109X373648
   Web of Science ®Google Scholar
• Jindal, N. and Singh, K. Joint image compression-encryption using discrete fractional transforms. Imaging Sci. J., 2014, 62/5, 265–272. doi: 10.1179/1743131X13Y.0000000062
   Web of Science ®Google Scholar
• Chang, C., Chuang, J. and Chung, C. Quadtree-segmented image compression method using vector quantization and cubic b-spline interpolation. Imaging Sci. J., 2004, 52/2, 106–116. doi: 10.1179/136821904225011591
   Web of Science ®Google Scholar
• Salarian, M., Nadernejad, E. and Naimi, H. A new modified fast fractal image compression algorithm. Imaging Sci. J., 2013, 61/2, 219–231. doi: 10.1179/1743131X11Y.0000000027
   Web of Science ®Google Scholar
• Zhang, J. Multi-source remote sensing data fusion: status and trends. Int. J. Image Data Fusion, 2010, 1/1, 5–24. doi: 10.1080/19479830903561035
   Google Scholar
• Reinoso, J. Pan-sharpening of quickbird satellite images using multiresolution techniques: wavelets, contourlets, and curvelets. Imaging Sci. J., 2010, 58/3, 125–135. doi: 10.1179/136821910X12651933390665
   Web of Science ®Google Scholar
• Gonzalez, R. C. and Woods, R. E. Digital image processing. 3rd edn, 2006 (Prentice-Hall Inc., Upper Saddle River, NJ)
   Google Scholar
• Standard, J. Information technology-digital compression and coding of continuous-tone still images-requirements and guidelines. International Telecommunication Union. CCITT Recommendation, 1992, 81, 09.
   Google Scholar
• Halsall, F. Multimedia communications: applications, networks, protocols, and standards, 2001, Pearson Education.
   Google Scholar
• Wallace, G. The JPEG still picture compression standard. IEEE Trans. Consumer Electron., 1992, 38, xviii–xxxiv. doi: 10.1109/30.125072
   Web of Science ®Google Scholar
• Hamilton, E. Jpeg file interchange format, 1992, C-Cube Microsystems.
   Google Scholar
• Choi, M. A new intensity–hue–saturation fusion approach to image fusion with a tradeoff parameter. IEEE Trans. Geosci. Remote Sens., 2006, 44/6, 1672–1682. doi: 10.1109/TGRS.2006.869923
   Web of Science ®Google Scholar