CN103179397A - Hyperspectral image compressing and restructuring device and method - Google Patents
Hyperspectral image compressing and restructuring device and method Download PDFInfo
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Abstract
The invention relates to hyperspectral image compressing and restructuring device and method. The method includes steps of firstly, subjecting each spectrum range of a hyperspectral image to three-level two-dimensional 9/7 integer discrete and lifting wavelet transformation; organizing wavelet coefficients to sections and blocks through CCDSD-IDC, encoding section header information and DC (direct current) coefficient initializing and AC (alternating current) coefficient depth of each block, extracting AC coefficient and residual DC coefficient bit plane simultaneously, and finally subjecting the AC coefficient and residual DC coefficient bit plane to distributed signal source encoding by a Slepian-Wolf encoder based on LDPC (low density parity check). The hyperspectral image compressing and restructuring device and method have the advantages that by adopting distributed signal source encoding strategy, complexity of the integral encoder is lowered, and the method is easy to implement through processors such as FPGA (field programmable gate array) and DSP (digital signal processor).
Description
Technical field
The present invention relates to the Remote Sensing Image Compression field, especially relate to a kind of Compression of hyperspectral images and reconfiguration device and method.
Background technology
Remote sensing hyperspectral image is that to same atural object, at hundreds of spectral coverages, (spectral resolution is generally 10 by imaging spectrometer
-2wavelength) three-dimensional data with spatial information and spectral information that upper imaging is obtained.The data of obtaining can improve abundant ground object detail, are widely used in the fields such as resource exploration, military surveillance and environmental protection.Along with the spectral resolution index of imaging spectrometer improves constantly, cause the high spectrum image data volume sharply to increase, existing spaceborne memory span is limited, and the satellite channel Bandwidth-Constrained can't adapt to the mass data of high-spectrum remote sensing.Therefore, must be compressed high-spectrum remote sensing.
The high spectrum image data have three kinds of redundancies: between spectral coverage, between redundancy, the interior spatial redundancy of spectral coverage and data, meet redundancy.Therefore, the purpose of Compression of hyperspectral images is eliminated this three kinds of redundancies exactly.At present, the high-spectrum remote sensing compression methods that adopt based on prediction, conversion and vector quantization, as 3D SPIHT, JPEG2000 etc. more.Yet the encoder amount of calculation of these methods is large, encoder complexity is high, the hardware realization is very complicated, and takies ample resources.For high-spectrum remote sensing on star, the image compression part completes on star, and the part that decompresses completes on ground, and on star, the disposal ability of compressor reducer, storage capacity and resource provisioning are all very limited.Therefore, under the prerequisite that the Compression of hyperspectral images on star need to be high in guaranteed efficiency and fault-tolerant ability is strong, there is low encoder complexity.
Summary of the invention
The present invention will solve how to weigh high spectrum compression algorithm compression performance and implementation complexity of the prior art, technical problem with the compression that is suitable for high spectrum image, a kind of complicated calculations that does not need to consider to eliminate the spectral coverage redundancy at coding side is provided, and being transferred to decoding end, it carries out, adopted the distributed source coding strategy, by the CCSDS-IDC compression algorithm, ideally be fused in distributed source coding, the encoder computing is simple, be easy to that hardware processor FPGA, DSP etc. realize, Compression of hyperspectral images and reconfiguration device and method.
In order to solve the problems of the technologies described above, technical scheme of the present invention is specific as follows:
Compression of hyperspectral images and reconfiguration device comprise:
1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 1#CCSDS-IDC bit plane encoder, the 1# Gray code conversion, 1# first-order linear filter, 2#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 2#CCSDS-IDC bit plane encoder, the 2# Gray code conversion, the compression bit rate assessment, Slepian-Wolf encoder based on LDPC, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 3#CCSDS-IDC bit plane encoder, the natural binary code conversion, the 1#CCSDS-IDC bit-plane decoder, Slepian-Wolf decoder based on LDPC, 1#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform, the 4#CCSDS-IDC bit plane encoder, the 3# Gray code conversion, 4#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, 2# first-order linear filter, the 2#CCSDS-IDC bit-plane decoder, 2#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform,
Present encoding spectral coverage X
ifor 1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation obtains 1 low frequency sub-band LL and 9 high-frequency sub-band HL1, HL2, HL3, LH1, LH2, LH3, HH1, HH1, HH1;
The wavelet sub-band coefficient can become some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding, simultaneously to DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane;
AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information;
With reference to spectral coverage X
i-1encode and be directly inputted in decoder to obtain Side information for 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder;
Decoder can be decoded according to Syndromes information and reference spectrum segment encode stream, obtains final reconstructed image;
3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and the 3#CCSDS-IDC bit plane encoder crucial spectral coverage that is used for encoding, so that decoding end and coding spectral coverage carry out combined decoding;
The first-order linear filter is used for according to X
i-1dope the approximation X ' of Xi
i, X '
iafter being encoded to spectral coverage X to be encoded
icompression bit rate assessment while carrying out the Slepian-Wolf encoder;
1# Gray code conversion, 2# Gray code conversion, 3# Gray code conversion are that the wavelet coefficient that DC coefficient remaining bit plane is corresponding transfers Gray code to by binary representation and means, to improve the reliability through the Slepian-Wolf encoder;
It can be binary code representation by the Gray code representation conversion by the DC coefficient of reconstruct that the 1# natural binary code is changed.
In technique scheme, the wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding, and wherein each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.
Compression of hyperspectral images and reconstructing method comprise the following steps:
At first, each spectral coverage of high spectrum image carries out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation;
Secondly, adopt the CCDSD-IDC method by the wavelet coefficient section of being organized into and piece, and paragraph header information, DC coefficient initialization and AC coefficient depth coding that will every, extract the AC coefficient simultaneously and remain DC coefficient bits plane;
Finally, the Slepian-Wolf encoder of employing based on LDPC is to AC coefficient and residue DC coefficient bits Planar realization distributed source coding.
In technique scheme, the method specifically comprises:
Step 1: high spectrum image is divided into to some groups, comprises A
1, A
2, A
3... A
n, each group has a crucial spectral coverage X
i-1, the spectral coverage group of take is encoded as unit, and at first encode A
1the spectral coverage group;
Step 2: by A
1crucial spectral coverage X
i-1, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder are directly encoded and are transferred to decoding end, obtain corresponding reconstruct spectral coverage in decoding end and are
Step 3: to A
1in other spectral coverage carry out absolute coding;
Step 4: by spectral coverage X '
iand X
icarry out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation, the wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding; To DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane;
Step 5: wavelet coefficient corresponding to residue DC coefficient bits plane is converted to Gray code by binary representation and means; Obtain compression bit rate according to the crossover probability of prediction spectral coverage and current spectral coverage, the code check assessment mainly completes the Rate Control effect;
Step 6:AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information;
Step 7: packed with crucial code check, Syndromes information and coefficient, send to decoding end;
Step 8: perform step 3, coding A
1in other spectral coverages, to A
1all spectral coverages are encoded;
Step 9: to next spectral coverage group, perform step 1 to 8, until A
nend-of-encode.
In technique scheme, in step 4, tissue becomes some sections and then take section as the unit absolute coding, and wherein each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.
The present invention has following beneficial effect:
Compression of hyperspectral images of the present invention and reconfiguration device and method, adopted the distributed source coding strategy, reduced the complexity of whole encoder, easily uses processor as realizations such as FPGA, DSP.
Compression of hyperspectral images of the present invention and reconfiguration device and method, adopt the CCDSD-IDC method by the wavelet coefficient section of being organized into and piece, and, by paragraph header information, DC coefficient initialization and the AC coefficient depth coding of every, extract AC coefficient and residue DC coefficient bits plane simultaneously.So not only hardware realizes simply having higher compression performance simultaneously.
Compression of hyperspectral images of the present invention and reconfiguration device and method, the Slepian-Wolf encoder of employing based on LDPC, to AC coefficient and residue DC coefficient bits Planar realization distributed source coding, not only has strong antijamming capability, and hardware is realized simply simultaneously.
The accompanying drawing explanation
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.
Fig. 1 is the illustrative view of functional configuration of the encoder in a kind of embodiment of Compression of hyperspectral images of the present invention and reconfiguration device and method.
Fig. 2 is Compression of hyperspectral images in the embodiment shown in Fig. 1 and the structural representation of reconfiguration device.
Embodiment
Invention thought of the present invention is: the principle of Compression of hyperspectral images of the present invention and reconfiguration device and method forms as shown in Figure 1.The present invention adopts the distributed source coding strategy, and at first, each spectral coverage of high spectrum image carries out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation; Secondly, adopt the CCDSD-IDC method by the wavelet coefficient section of being organized into and piece, and paragraph header information, DC coefficient initialization and AC coefficient depth coding that will every, extract the AC coefficient simultaneously and remain DC coefficient bits plane; Finally, the Slepian-Wolf encoder of employing based on LDPC is to AC coefficient and residue DC coefficient bits Planar realization distributed source coding.
Below in conjunction with accompanying drawing, the present invention is described in detail.
As illustrated in fig. 1 and 2, a kind of Compression of hyperspectral images of the present invention and reconfiguration device comprise:
1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 1#CCSDS-IDC bit plane encoder, the 1# Gray code conversion, 1# first-order linear filter, 2#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 2#CCSDS-IDC bit plane encoder, the 2# Gray code conversion, the compression bit rate assessment, Slepian-Wolf encoder based on LDPC, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 3#CCSDS-IDC bit plane encoder, the natural binary code conversion, the 1#CCSDS-IDC bit-plane decoder, Slepian-Wolf decoder based on LDPC, 1#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform, the 4#CCSDS-IDC bit plane encoder, the 3# Gray code conversion, 4#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, 2# first-order linear filter, the 2#CCSDS-IDC bit-plane decoder, 2#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform forms, it is characterized in that present encoding spectral coverage X
iadopt 1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation to obtain 1 low frequency sub-band LL and 9 high-frequency sub-band HL1, HL2, HL3, LH1, LH2, LH3, HH1, HH1, HH1.The wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding.Each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.Simultaneously to DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane.AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information; With reference to spectral coverage (also claiming crucial spectral coverage) X
i-1adopting 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder to encode is directly inputted in decoder in order to obtain Side information.Decoder is decoded according to Syndromes information and reference spectrum segment encode stream, obtains final reconstructed image.
Described 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and the 3#CCSDS-IDC bit plane encoder crucial spectral coverage that is used for encoding, so that decoding end and coding spectral coverage carry out combined decoding.
Described first-order linear filter is used for according to X
i-1dope the approximation X ' of Xi
i, X '
iafter being encoded to spectral coverage X to be encoded
icompression bit rate assessment while carrying out the Slepian-Wolf encoder.
Described 1# Gray code conversion, 2# Gray code conversion, 3# Gray code conversion are that the wavelet coefficient that DC coefficient remaining bit plane is corresponding transfers Gray code to by binary representation and means, to improve the reliability through the Slepian-Wolf encoder.
It is by the Gray code representation conversion, to be binary code representation by the DC coefficient of reconstruct that described 1# natural binary code is changed.
Compression of hyperspectral images of the present invention and reconstructing method comprise the following steps:
Step 1: high spectrum image is divided into to some groups of (A
1, A
2, A
3... A
n), each group has a crucial spectral coverage X
i-1, the spectral coverage group of take is encoded as unit.At first A encodes
1the spectral coverage group.
Step 2: by A
1crucial spectral coverage X
i-1, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder are directly encoded and are transferred to decoding end, obtain corresponding reconstruct spectral coverage in decoding end and are
Step 3: to A
1in other spectral coverage carry out absolute coding.If the present encoding spectral coverage is X
i.Utilize crucial spectral coverage X
i-1adopt the first-order linear filter to obtain spectral coverage X
ithe approximate spectral coverage X ' of maximum
i, i.e. X '
i=a * X
i-1+ b.Coefficient a and b are by spectral coverage X
iwith spectral coverage X
i-1use least square method to be solved.Adopt and use the same method in decoding end,
Step 4: by spectral coverage X '
iand X
icarry out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation, the wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding.Each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.Simultaneously to DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane.
Step 5: wavelet coefficient corresponding to residue DC coefficient bits plane is converted to Gray code by binary representation and means.Simultaneously, according to the crossover probability of prediction spectral coverage and current spectral coverage, obtain compression bit rate, the code check assessment mainly completes the Rate Control effect.
Step 6:AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information.
Step 7: last and crucial code check, Syndromes information and coefficient are packed, and send to decoding end.
Step 8: perform step 3, coding A
1in other spectral coverages, to A
1all spectral coverages are encoded.
Step 9: to next spectral coverage group, perform step 1 to 8, until A
nend-of-encode.
Compression of hyperspectral images of the present invention and reconfiguration device and method, adopted the distributed source coding strategy, reduced the complexity of whole encoder, easily uses processor as realizations such as FPGA, DSP.
Compression of hyperspectral images of the present invention and reconfiguration device and method, adopt the CCDSD-IDC method by the wavelet coefficient section of being organized into and piece, and, by paragraph header information, DC coefficient initialization and the AC coefficient depth coding of every, extract AC coefficient and residue DC coefficient bits plane simultaneously.So not only hardware realizes simply having higher compression performance simultaneously.
Compression of hyperspectral images of the present invention and reconfiguration device and method, the Slepian-Wolf encoder of employing based on LDPC is to AC coefficient and residue DC coefficient bits Planar realization distributed source coding, not only have strong antijamming capability, hardware is realized simple simultaneously.
Obviously, above-described embodiment is only for example clearly is described, and is not the restriction to execution mode.For those of ordinary skill in the field, can also make other changes in different forms on the basis of the above description.Here exhaustive without also giving all execution modes.And the apparent variation of being extended out thus or change are still among the protection range in the invention.
Claims (5)
1. Compression of hyperspectral images and reconfiguration device, is characterized in that, comprising:
1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 1#CCSDS-IDC bit plane encoder, the 1# Gray code conversion, 1# first-order linear filter, 2#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 2#CCSDS-IDC bit plane encoder, the 2# Gray code conversion, the compression bit rate assessment, Slepian-Wolf encoder based on LDPC, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, the 3#CCSDS-IDC bit plane encoder, the natural binary code conversion, the 1#CCSDS-IDC bit-plane decoder, Slepian-Wolf decoder based on LDPC, 1#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform, the 4#CCSDS-IDC bit plane encoder, the 3# Gray code conversion, 4#3 level two dimension 9/7 integer Discrete lifting wavelet transformation, 2# first-order linear filter, the 2#CCSDS-IDC bit-plane decoder, 2#3 level two dimension 9/7 integer Discrete lifting inverse wavelet transform,
Present encoding spectral coverage Xi is that 1#3 level two dimension 9/7 integer Discrete lifting wavelet transformation obtains 1 low frequency sub-band LL and 9 high-frequency sub-band HL1, HL2, HL3, LH1, LH2, LH3, HH1, HH1, HH1;
The wavelet sub-band coefficient can become some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding, simultaneously to DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane;
AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information;
With reference to spectral coverage X
i-1encode and be directly inputted in decoder to obtain Side information for 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder;
Decoder can be decoded according to Syndromes information and reference spectrum segment encode stream, obtains final reconstructed image;
3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and the 3#CCSDS-IDC bit plane encoder crucial spectral coverage that is used for encoding, so that decoding end and coding spectral coverage carry out combined decoding;
The first-order linear filter is used for according to X
i-1dope the approximation X ' of Xi
i, X '
iafter being encoded to spectral coverage X to be encoded
icompression bit rate assessment while carrying out the Slepian-Wolf encoder;
1# Gray code conversion, 2# Gray code conversion, 3# Gray code conversion are that the wavelet coefficient that DC coefficient remaining bit plane is corresponding transfers Gray code to by binary representation and means, to improve the reliability through the Slepian-Wolf encoder;
It can be binary code representation by the Gray code representation conversion by the DC coefficient of reconstruct that the 1# natural binary code is changed.
2. Compression of hyperspectral images according to claim 1 and reconfiguration device, is characterized in that,
The wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding, and wherein each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.
3. Compression of hyperspectral images and reconstructing method, is characterized in that, comprises the following steps:
At first, each spectral coverage of high spectrum image carries out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation;
Secondly, adopt the CCDSD-IDC method by the wavelet coefficient section of being organized into and piece, and paragraph header information, DC coefficient initialization and AC coefficient depth coding that will every, extract the AC coefficient simultaneously and remain DC coefficient bits plane;
Finally, the Slepian-Wolf encoder of employing based on LDPC is to AC coefficient and residue DC coefficient bits Planar realization distributed source coding.
4. Compression of hyperspectral images according to claim 3 and reconstructing method, is characterized in that, the method specifically comprises:
Step 1: high spectrum image is divided into to some groups, comprises A
1, A
2, A
3... A
n, each group has a crucial spectral coverage X
i-1, the spectral coverage group of take is encoded as unit, and at first encode A
1the spectral coverage group;
Step 2: by A
1crucial spectral coverage X
i-1, 3#3 level two dimension 9/7 integer Discrete lifting wavelet transformation and 3#CCSDS-IDC bit plane encoder are directly encoded and are transferred to decoding end, obtain corresponding reconstruct spectral coverage in decoding end and are
Step 3: to A
1in other spectral coverage carry out absolute coding;
Step 4: by spectral coverage X '
iand X
icarry out 3 grades of two dimensions, 9/7 integer Discrete lifting wavelet transformation, the wavelet sub-band coefficient becomes some sections through 1#CCSDS-IDC bit plane encoder tissue, then take section as the unit absolute coding; To DC coefficient initialization, paragraph header information, AC coefficient bit depth coding, and extract AC coefficient and residue DC coefficient bits plane;
Step 5: wavelet coefficient corresponding to residue DC coefficient bits plane is converted to Gray code by binary representation and means; Obtain compression bit rate according to the crossover probability of prediction spectral coverage and current spectral coverage, the code check assessment mainly completes the Rate Control effect;
Step 6:AC coefficient and residue DC coefficient bits plane are used the Slepian-Wolf encoder based on LDPC to be encoded, and obtain Syndromes information;
Step 7: packed with crucial code check, Syndromes information and coefficient, send to decoding end;
Step 8: perform step 3, coding A
1in other spectral coverages, to A
1all spectral coverages are encoded;
Step 9: to next spectral coverage group, perform step 1 to 8, until A
nend-of-encode.
5. Compression of hyperspectral images according to claim 4 and reconstructing method, is characterized in that, in step 4, tissue becomes some sections and then take section as the unit absolute coding, and wherein each section is comprised of 16 pieces, and every is comprised of 1 DC coefficient and 63 AC coefficients.
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| CN106375763A (en) * | 2016-11-25 | 2017-02-01 | 合肥工业大学 | Slepian-Wolf technology based video encryption-decryption method and encryption-decryption system thereof |
| CN108133500A (en) * | 2017-12-22 | 2018-06-08 | 杭州电子科技大学 | A kind of splits' positions reconstructing method towards plant EO-1 hyperion |
| CN110751671A (en) * | 2018-07-23 | 2020-02-04 | 中国科学院长春光学精密机械与物理研究所 | Target tracking method based on kernel correlation filtering and motion estimation |
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