26 August 2005 Evaluating residual coding with JPEG2000 for L-infinity driven hyperspectral image compression
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Abstract
This paper presents a study on the compression of hyperspectral satellite data using JPEG 2000 and residual encoding (RE). The first step in the process is to apply a decorrelating transform in the spectral-direction or z-direction. In most cases in this study, the Karhunen-Loeve Transform (KLT) is used. For comparison, some examples are also included where the discrete wavelet transform (DWT) is used for this purpose as well as examples with a purely 2-D approach that uses no z-direction transform. Bit-rate allocation techniques are used in order to take advantage of the energy compaction obtained when applying a transform in the z-direction. The transformed slices and their corresponding bit rates are input into JPEG 2000 in order to obtain the compressed bit stream. In this study, the compressed bit stream is decompressed at the encoder side in order to compute the recovered data. These data are then subtracted from the original data in order to calculate the residuals, which are then quantized and losslessly encoded separately using JPEG2000 itself in order to control the maximum absolute error (MAE). An analysis between using and omitting residual encoding with respect to MAE is included. It is observed that a decrease in the MAE by a factor of 3 is achieved for this data with very small overhead when the residual encoding is utilized. The two data sets used in this study are the well known Cuprite radiance imagery from AVIRIS and a set from the Hyperion satellite system, both of which are available in 16 bits per value form.
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Aldo Lucero, Aldo Lucero, Sergio Cabrera, Sergio Cabrera, Edward Vidal, Edward Vidal, Alberto Aguirre, Alberto Aguirre, } "Evaluating residual coding with JPEG2000 for L-infinity driven hyperspectral image compression", Proc. SPIE 5889, Satellite Data Compression, Communications, and Archiving, 588903 (26 August 2005); doi: 10.1117/12.617397; https://doi.org/10.1117/12.617397
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