Citation
Abstract
This article briefly describes a set of compressed, then reconstructed, test Images submitted to the CRAF/Cassini project as part of its evaluation of near-lossless high-compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images have been compressed, then reconstructed with high quality (root-mean-square error of approximately one or two gray levels on an 8-bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wider range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.
Details
- Volume
- 42-104
- Published
- February 15, 1991
- Pages
- 88–97
- File Size
- 406.5 KB