Satellite image compression using wavelet

Alb. Joko Santoso; F. Soesianto; B. Yudi Dwiandiyanto

doi:10.1117/12.855734

26 February 2010 Satellite image compression using wavelet

Alb. Joko Santoso, F. Soesianto, B. Yudi Dwiandiyanto

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75463N (2010) https://doi.org/10.1117/12.855734
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

Abstract

Image data is a combination of information and redundancies, the information is part of the data be protected because it contains the meaning and designation data. Meanwhile, the redundancies are part of data that can be reduced, compressed, or eliminated. Problems that arise are related to the nature of image data that spends a lot of memory. In this paper will compare 31 wavelet function by looking at its impact on PSNR, compression ratio, and bits per pixel (bpp) and the influence of decomposition level of PSNR and compression ratio. Based on testing performed, Haar wavelet has the advantage that is obtained PSNR is relatively higher compared with other wavelets. Compression ratio is relatively better than other types of wavelets. Bits per pixel is relatively better than other types of wavelet.

Citation Download Citation

Alb. Joko Santoso, F. Soesianto, and B. Yudi Dwiandiyanto "Satellite image compression using wavelet", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463N (26 February 2010); https://doi.org/10.1117/12.855734

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