Region-based image coding with multiple algorithms
| Autor: | Craig Underwood, Maria Petrou, Sei-ichiro Kamata, Peixin Hou |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
business.industry
Computer science Multispectral image ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Wavelet transform computer.file_format JPEG Multispectral pattern recognition Adaptive coding General Earth and Planetary Sciences Codec Computer vision Artificial intelligence Electrical and Electronic Engineering business computer Algorithm Data compression |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 39:562-570 |
| ISSN: | 0196-2892 |
| DOI: | 10.1109/36.911114 |
| Popis: | The wide usage of small satellite imagery, especially its commercialization, makes data-based onboard compression not only meaningful but also necessary in order to solve the bottleneck between the huge volume of data generated onboard and the very limited downlink bandwidth. The authors propose a method that encodes different regions with different algorithms. The authors use three shape-adaptive image compression algorithms as the candidates. The first one is a JPEG-based algorithm, the second one is based on the object-based wavelet transform method proposed by Katata et al. (1997), and the third adopts Hilbert scanning of the regions of interest followed by one-dimensional (1-D) wavelet transform. The three algorithms are also applied to the full image so that one can compare their performance on a whole rectangular image. The authors use eight Landsat TM multispectral images and another 12 small satellite single-band images as their data set. The results show that these compression algorithms have significantly different performance for different regions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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