Wavelet Still Image Coding: A Baseline MSE and HVS Approach

J. Lu, R. Algazi, and R. Estes, “Comparison of Wavelet Image Coders Using the Picture Quality Scale,” UC-Davis preprint, 1995.Google Scholar

M. Antonini et al, “Image Coding Using Wavelet Transform,” IEEE Trans. Image Proc., pp. 205–220, April, 1992.Google Scholar

I. Daubechies, Ten Lectures on Wavelets, SIAM, 1992.Google Scholar

B. Chitraprasert, and K. Rao, “Human Visual Weighted Progressive Image Transmission,” IEEE Trans. Comm., vol. 38, pp. 1040–1044, 1990.Google Scholar

“Wavelet Scalar Quantization Fingerprint Image Compression Standard,” Criminal Justice Information Services, FBI, March, 1993.Google Scholar

A. Gersho and R. Gray, Vector Quantization and Signal Compression, Kluwer, 1992.Google Scholar

N. Griswold, “Perceptual Coding in the Cosine Transform Domain,” Opt. Eng., v. 19, pp. 306–311, 1980.Google Scholar

J. Huang and P. Schultheiss, “Block Quantization of Correlated Gaussian Variables,” IEEE Trans. Comm., CS-11, pp. 289–296, 1963.Google Scholar

W. Pennebaker and J. Mitchell, JPEG Still Image Data Compression Standard, Van Nostrand, 1993.Google Scholar

T. Lane et al, The Independent JPEG Group Software. ftp://ftp.uu.net/graphics/jpeg.

R. Kam and P. Wong, “Customized JPEG Compression for Grayscale Printing,”. Data Comp. Conf. DCC-94, IEEE, pp. 156–165, 1994.Google Scholar

A. Lewis and G. Knowles, “Image Compression Using the 2-D Wavelet Transform,” IEEE Trans. Image Proc., pp. 244–250, April. 1992.Google Scholar

D. LeGall and A. Tabatabai, “Subband Coding of Digital Images Using Symmetric Short Kernel Filters and Arithmetic Coding Techniques,” Proc. ICASSP, IEEE, pp. 761–765, 1988.Google Scholar

N. Lohscheller, “A Subjectively Adapted Image Communication System,” IEEE Trans. Comm., COM-32, pp. 1316–1322, 1984.Google Scholar

E. Majani, “Biorthogonal Wavelets for Image Compression,” Proc. SPIE, VCIP-94, 1994.Google Scholar

J. Mannos and D. Sakrison, “The Effect of a Visual Fidelity Criterion on the Encoding of Images,” IEEE Trans. Info. Thry, IT-20, pp. 525–536, 1974.Google Scholar

K. Ngan, K. Leong, and H. Singh, “Adaptive Cosine Transform Coding of Images in Perceptual Domain,” IEEE Trans. Acc. Sp. Sig. Proc., ASSP-37, pp. 1743–1750, 1989.Google Scholar

N. Nill, “A Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment,” IEEE Trans. Comm., pp. 551–557, June, 1985.Google Scholar

A. Zandi et al, “CREW: Compression with Reversible Embedded Wavelets,” Proc. Data Compression Conference 95, IEEE, March, 1995.Google Scholar

A. Said and W. Pearlman, “A new, fast, and efficient image codec based on set partitioning in hierarchical trees,” IEEE Trans. Circuits and Systems for Video Technology, vol. 6, pp. 243–250, June 1996.Google Scholar

E. Selwyn and J. Tearle, em Proc. Phys. Soc., Vo. 58, no. 33, 1946.Google Scholar

J. Shapiro, “Embedded Image Coding Using Zerotrees of Wavelet Coefficients,” IEEE Trans. Signal Proc., pp. 3445–3462, December, 1993.Google Scholar

J. Shapiro, “Smart Compression Using the Embedded Zerotree Wavelet (EZW) Algorithm,” Proc. Asilomar Conf. Sig., Syst. and Comp., IEEE, pp. 486–490, 1993.Google Scholar

S. Mallat and F. Falcon, “Understanding Image Transform Codes,” IEEE Trans. Image Proc., submitted, 1997.Google Scholar

S. LoPresto, K. Ramchandran, and M. Orchard, “Image Coding Based on Mixture Modelling of Wavelet Coefficients and a Fast Estimation-Quantization Framework,” DCC97, Proc. Data Comp. Conf., Snowbird, UT, pp. 221–230, March, 1997.Google Scholar

Y. Shoham and A. Gersho, “Efficient Bit Allocation for an Arbitrary Set of Quantizers,” IEEE Trans. ASSP, vol. 36, pp. 1445–1453, 1988.Google Scholar

A. Docef et al, “Multiplication-Free Subband Coding of Color Images,” Proc. Data Compression Conference 95, IEEE, pp. 352–361, March, 1995.Google Scholar

W. Chung et al, “A New Approach to Scalable Video Coding,” Proc. Data Compression Conference 95, IEEE, pp. 381–390, March, 1995.Google Scholar

M. Smith, “ATR and Compression,” Workshop on Clipping Service, MITRE Corporation, July, 1995.Google Scholar

G. Strang and T. Nguyen, Wavelets and Filter Banks, Cambridge-Wellesley Press, 1996.Google Scholar

P. Topiwala et al, Fundamentals of Wavelets and Applications, IEEE Educa-tional Video, September, 1995.Google Scholar

P. Topiwala et al, “Region of Interest Compression Using Pyramidal Coding Schemes,” Proc. SPIE-San Diego, Mathematical Imaging, July, 1995.Google Scholar

K. Tzou, T. Hsing and J. Dunham, “Applications of Physiological Human Visual System Model to Image Compression,” Proc. SPIE 504, pp. 419–424, 1984.Google Scholar

J. Villasenor et al, “Filter Evaluation and Selection in Wavelet Image Compression,” Proc. Data Compression Conference, IEEE, pp. 351–360, March, 1994.Google Scholar

J. Villasenor et al, “Wavelet Filter Evaluation for Image Compression,” IEEE Trans. Image Proc., August, 1995.Google Scholar

M. Vetterli and J. Kovacevic, Wavelets and Subband Coding, Prentice-Hall, 1995.Google Scholar

A. Watson et al, “Visibility of Wavelet Quantization Noise,” NASA Ames Research Center preprint 1996. http://www.vision.arc.nasa.gov/personnel/watson/watson.html

I. Witten et al, “Arithmetic Coding for Data Compression,” Comm. ACM, IEEE, pp. 520–541, June, 1987.Google Scholar

Z. Xiong et al, “Joint Optimization of Scalar and Tree-Structured Quantization of Wavelet Image Decompositions,” Proc. Asilomar Conf. Sig., Syst., and Comp., IEEE, November, 1993.Google Scholar