Abstract
Recently, the discrete wavelet transforms- (DWT-) based compressor, such as JPEG2000 and CCSDS-IDC, is widely seen as the state of the art compression scheme for charge coupled devices (CCD) camera. However, CCD images project on the DWT basis to produce a large number of large amplitude high-frequency coefficients because these images have a large number of complex texture and contour information, which are disadvantage for the later coding. In this paper, we proposed a low-complexity posttransform coupled with compressing sensing (PT-CS) compression approach for remote sensing image. First, the DWT is applied to the remote sensing image. Then, a pair base posttransform is applied to the DWT coefficients. The pair base are DCT base and Hadamard base, which can be used on the high and low bit-rate, respectively. The best posttransform is selected by the l p-norm-based approach. The posttransform is considered as the sparse representation stage of CS. The posttransform coefficients are resampled by sensing measurement matrix. Experimental results on on-board CCD camera images show that the proposed approach significantly outperforms the CCSDS-IDC-based coder, and its performance is comparable to that of the JPEG2000 at low bit rate and it does not have the high excessive implementation complexity of JPEG2000.
Highlights
Charge coupled devices (CCD) camera is heading for a high spatial resolution, high radiation resolution, large field of view, and wide coverage development [1,2,3]
We proposed a low-complexity posttransform coupled with compressing sensing (PT-compression sensing (CS)) compression approach for remote sensing image
The posttransform coefficients are resampled by sensing measurement matrix
Summary
Charge coupled devices (CCD) camera is heading for a high spatial resolution, high radiation resolution, large field of view, and wide coverage development [1,2,3]. This approach can remove the redundancy between wavelets coefficients, which can improve compression performance Because it processes a 16-coefficient block and only carries out dot product operation, it does not require the large amount memories and could implement on hardware. To adapt on-board application, Delaunay et al in [42,43,44] proposed a compression scheme using BPE from the CCSDS recommendation to code posttransform coefficients. They only apply the posttransform to the grandchildren coefficients, so that the compression performance is not that much better.
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