Lossless Compression of a Desktop Image For Transmission

We have presented a desktop image compression algorithm for real-time applications such as remote desktop access by desktop image transmission. The desktop image is called as a complex image, because one 800 X 600 true color image has a size of approximately 1.54 MB with pictures and text. The algorithm is called as group extraction and coding (GEC). Real-time image transmission requires that the compression algorithm should not only achieve high compression ratio, but also have excellent visual quality and low complexity. In the extraction/ separation phase of the complex desktop image, we have separated the blocks into picture and text/graphics blocks by thresholding the number of colors contained in each block. Text/graphics block classes have been compressed by using a wavelet based SPIHT lossless coding algorithm, while picture block classes, by JPEG algorithm. The compressed blocks have been combined to form a single bit stream. Experimental results have shown that the GEC has very low complexity and provides visually excellent lossless quality with very good compression ratios.

[1]  Daniel P. Huttenlocher,et al.  Digipaper: a versatile color document image representation , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[2]  Pengwei Hao,et al.  Compound image compression for real-time computer screen image transmission , 2005, IEEE Transactions on Image Processing.

[3]  Trac D. Tran,et al.  Optimizing block-thresholding segmentation for multilayer compression of compound images , 2000, IEEE Trans. Image Process..

[4]  Hui Cheng,et al.  Rate-distortion-based segmentation for MRC compression , 2001, IS&T/SPIE Electronic Imaging.

[5]  Trac D. Tran,et al.  Optimizing block-threshold segmentation for MRC compression , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[6]  Yann LeCun,et al.  DjVu: analyzing and compressing scanned documents for Internet distribution , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[7]  Edward K. Wong,et al.  Check image compression using a layered coding method , 1998, J. Electronic Imaging.

[8]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[9]  K. Ashok Babu,et al.  Modified SPIHT Algorithm for Wavelet Packet Image Coding , 2009 .

[10]  Ming Xu,et al.  Mixed raster content (MRC) model for compound image compression , 1998, Electronic Imaging.

[11]  Xin Li,et al.  On the study of lossless compression of computer generated compound images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  Debargha Mukherjee,et al.  Low complexity guaranteed fit compound document compression , 2002, Proceedings. International Conference on Image Processing.

[13]  Xin Li,et al.  Block-based segmentation and adaptive coding for visually lossless compression of scanned documents , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[14]  Hui Cheng,et al.  Document compression using rate-distortion optimized segmentation , 2001, J. Electronic Imaging.

[15]  Yoshua Bengio,et al.  High quality document image compression with "DjVu" , 1998, J. Electronic Imaging.