Transform coding techniques for lossy hyperspectral data compression

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (SUBMITTED DEC. 2005) 25
TABLE III
COMPARISON BETWEEN THE PROPOSED TECHNIQUE AND SPECK - SNR (DB).
Coding scheme / Rate (bpp) 0.1 0.2 0.5 1 2 3 4
Jasper Ridge - scene 1
Proposed scheme (KLT) 27.97 34.02 40.77 45.50 51.24 56.86 57.77
Proposed scheme (low-complexity KLT) 27.90 33.85 40.69 45.35 50.99 56.59 57.84
DWT1D2D [16] 22.31 26.55 34.31 40.41 47.31 52.56 57.56
3D-SPECK 19.70 23.66 31.75 38.55 46.00 48.59 52.36
Moffett Field - scene 1
Proposed scheme (KLT) 22.17 32.54 42.17 47.46 53.45 58.92 61.04
Proposed scheme (low-complexity KLT) 22.19 32.56 42.08 47.40 53.27 58.73 61.10
DWT1D2D [16] 17.24 22.34 32.22 40.85 48.76 53.98 59.25
3D-SPECK 16.67 21.52 29.91 38.60 47.18 51.27 55.57
Moffett Field - scene 3
Proposed scheme (KLT) 16.12 25.34 36.32 42.87 49.75 55.08 56.92
Proposed scheme (low-complexity KLT) 16.10 25.32 36.21 42.83 49.62 54.89 57.05
DWT1D2D [16] 12.86 17.91 27.53 36.37 45.09 50.75 55.87
3D-SPECK 12.60 17.98 26.99 35.37 40.10 46.71 50.79
vector, and r i those of the reference vector.
Following the procedure in [30], [11], [31], we have selected an area in scene 1 of Jasper Ridge,
and have applied the k-means clustering method [32], [33] to evaluate the centroids of three clusters,
namely asphalt, water and vegetation. Subsequently, we have employed these three selected centroids
as reference vectors in the SAM method.
In Tab. IV we report the classification performance in terms of percentage of pixels assigned to
the same cluster in the reconstructed image with respect to the original one. It can be noticed that
the performance reflects quite closely the result discussed above in terms of PSNR, in that, in the
vast majority of cases, a higher PSNR results into a smaller classification error; this is consistent
with the results in [17], and confirms that MSE-based metrics are reasonably good indicators of
the performance degradation caused by compression artifacts. These results, although without any
presumption of being exhaustive, indeed indicate that for this application the proposed scheme yields
improved performance also in terms of classification results, making the proposed technique very
competitive in terms of complexity, compression performance, and remote sensing image quality.
In Fig. 16 one can see the results of the classification procedure applied to the original image, to
the reconstructed image with full-complexity KLT at rate of 1 bpp, and to the reconstructed image