Paper
3 March 1995 Low-bit-rate image coding using sketch image and JBIG
Guang Deng, Laurence W. Cahill
Author Affiliations +
Proceedings Volume 2418, Still-Image Compression; (1995) https://doi.org/10.1117/12.204131
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States
Abstract
At low bit rates most current image coding techniques will generate a smooth image where some of the important details of the original image are lost. For example, the compression of an image by JPEG down to a bit rate of 0.1 to 0.2 bit/pel usually results in a significant loss of detail and an annoying blocking effect. The basic idea in this paper is that in applications where the detail information in a low bit rate coded image is of more concern than the gray scale information, it is necessary to encode the former and disregard the latter. Based on the logarithmic image processing model, we have recently proposed a novel algorithm to generate a binary image (called the sketch image) from a gray scale image. We have shown that the sketch image retains much more information of the original image than those images generated by other image binarization techniques such as simple thresholding, ordered dither and error diffusion. In this paper, we further study the sketch image algorithm and propose a simple data compression scheme which incorporates a decimation and interpolation algorithm and the JBIG algorithm. Experimental results have shown that at low bit rate (about 0.1 bit/pel) the proposed algorithm preserves the fine details of the original image at the expense of loss of grey scale information.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guang Deng and Laurence W. Cahill "Low-bit-rate image coding using sketch image and JBIG", Proc. SPIE 2418, Still-Image Compression, (3 March 1995); https://doi.org/10.1117/12.204131
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Cited by 6 scholarly publications.
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KEYWORDS
Image compression

Image filtering

Binary data

Image processing

Data compression

Diffusion

Image quality

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