A generic psychovisual error threshold for the quantization table generation on JPEG image compression

The quantization process is a main part of image compression to control visual quality and the bit rate of the image output. The JPEG quantization tables are obtained from a series of psychovisual experiments to determine a visual threshold. The visual threshold is useful in handling the intensity level of the colour image that can be perceived visually by the human visual system. This paper will investigate a psychovisual error threshold at DCT frequency on the grayscale image. The DCT coefficients are incremented one by one for each frequency order. Whereby, the contribution of DCT coefficients to the error reconstruction will be a primitive pyschovisual error. At certain threshold being set on this psychovisual error, the new quantization table can be generated. The experimental results show that the new quantization table from psychovisual error threshold for DCT basis functions gives better quality image at lower average bit length of Huffman code than standard JPEG image compression.

[1]  Jun Sun,et al.  Rate-distortion Optimized Trellis-Coded Quantization , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[2]  Barry G. Sherlock,et al.  Optimum DCT quantization , 1993, [Proceedings] DCC `93: Data Compression Conference.

[3]  Robert M. Hierons,et al.  JPEG Steganography: A Performance Evaluation of Quantization Tables , 2009, 2009 International Conference on Advanced Information Networking and Applications.

[4]  Jesse D. Kornblum Using JPEG quantization tables to identify imagery processed by software , 2008, Digit. Investig..

[5]  Alan C. Bovik,et al.  The Essential Guide to Image Processing , 2009, J. Electronic Imaging.

[6]  Herbert Lohscheller,et al.  A Subjectively Adapted Image Communication System , 1984, IEEE Trans. Commun..

[7]  Joan L. Mitchell,et al.  JPEG: Still Image Data Compression Standard , 1992 .

[8]  Jianqin Zhou,et al.  On discrete cosine transform , 2011, ArXiv.

[9]  Kannan Ramchandran,et al.  JPEG optimization using an entropy-constrained quantization framework , 1995, Proceedings DCC '95 Data Compression Conference.

[10]  Lai-Man Po,et al.  A New Partial Codeword Updating Scheme Based on Rate-Distortion Optimization for Adaptive Vector Quantization , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[11]  Kannan Ramchandran,et al.  Rate-distortion optimal fast thresholding with complete JPEG/MPEG decoder compatibility , 1994, IEEE Trans. Image Process..

[12]  David A. Huffman,et al.  A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.

[13]  Yuebing Jiang,et al.  JPEG image compression using quantization table optimization based on perceptual image quality assessment , 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).