Satellite multispectral image compression based on removing sub-bands

Abstract This paper presents an efficient technique for satellite multispectral image compression aiming at reducing the size of storage of multispectral images with high-quality reconstruction. The proposed technique is based on removing sub-bands before compression. The removed sub-bands are determined using the correlation coefficients between bands. In the compression process, we use the Discrete Wavelet Transform (DWT) followed by an entropy coder (e.g., a Huffman or an arithmetic encoder) for the most correlated bands. Moreover, we use JPEG2000 to compress the rest of bands with Principal Component Analysis (PCA) as a spectral decorrelation transform. Enhanced Thematic Mapper plus (ETM+) satellite multispectral images are used for the validation of the proposed technique. Experiments results demonstrate that the proposed technique improves the average multispectral image quality by 3–11 dB. The experimental results verify the effectiveness of the proposed technique.

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