Band Ordering in Lossless Compression of Multispectral Images
IEEE Transactions on Computers
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In present era the multi/hype spectral images are being increasingly used in traditional and key application areas such as remote sensing and geosciences. These images contain geographical information and reflect the complexity of geographical features and spatial structures. As the means of observing and describing geographical phenomena, the rapid development of remote sensing has provided an enormous amount of geographical information which is highly correlated. The massive wealth of information is very useful in a variety of applications but the sheer bulk of this information has increased beyond what can be analyzed and used efficiently and effectively. This uneven increase in the technologies of gathering and analyzing information has created difficulties in its storage, transfer, and processing. The paper attempts to develop an application-specific data compression technique that exploits inter-band correlation and then applies HAAR wavelet to selected bands of the multispectral image 'orlea_s.lan'. We finally calculate the loss functions in statistics like MSE, MAE, RMSE and PSNR.