Evaluating the Quality of Compression in Very High Resolution Satellite Images Using Different Compression Methods

Abstract:

The rapid growth of remote sensing technology has a great advantage in producing high resolution images which are huge in data volume. Due to the huge volume it is tedious to store and transmit the data. In order to overcome this, a good compression algorithm should be used to compress the data before storing are transmitting. In this paper we have chosen seven different very high resolution satellite images namely Worldview 3, Worldview 2, GeoEye-1, Worldview 1, Pleiades, Quick Bird and IKONOS they are compressed using three different compression methods JPEG, SPIHT and JPEG2000. The Mean square Error, Signal to noise Ratio and Peak Signal to Noise Ratio are calculated to evaluate the quality of the compression methods in very high resolution satellite images.

• Periodical: International Journal of Engineering Research in Africa (Volume 19)
• Pages: 91-102
• DOI: https://doi.org/10.4028/www.scientific.net/JERA.19.91
• Online since: October 2015
• Authors: S. Sanjith*, R. Ganeshan
• Keywords: JPEG, JPEG2000, Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Satellite Image Compression, Signal to Noise Ratio (SNR), SPIHT

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