Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding
Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Abdelwahab, Ahmed A [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Rechteinformationen: |
Nutzungsrecht: © 2017, World Scientific Publishing Company |
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| Übergeordnetes Werk: |
Enthalten in: International journal of image and graphics - Singapore [u.a.] : World Scientific, 2001, 17(2017), 3 |
|---|---|
| Übergeordnetes Werk: |
volume:17 ; year:2017 ; number:3 |
| Links: |
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| DOI / URN: |
10.1142/S0219467817500176 |
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OLC1999748395 |
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| 520 | |a Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. | ||
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10.1142/S0219467817500176 doi PQ20171228 (DE-627)OLC1999748395 (DE-599)GBVOLC1999748395 (PRQ)worldscientific_primary_S02194678175001760 (KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect DE-627 ger DE-627 rakwb eng 610 ZDB 54.74 bkl Abdelwahab, Ahmed A verfasserin aut Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. Nutzungsrecht: © 2017, World Scientific Publishing Company Enthalten in International journal of image and graphics Singapore [u.a.] : World Scientific, 2001 17(2017), 3 (DE-627)346833507 (DE-600)2078011-4 (DE-576)9346833505 0219-4678 nnns volume:17 year:2017 number:3 http://dx.doi.org/10.1142/S0219467817500176 Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.74 AVZ AR 17 2017 3 |
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10.1142/S0219467817500176 doi PQ20171228 (DE-627)OLC1999748395 (DE-599)GBVOLC1999748395 (PRQ)worldscientific_primary_S02194678175001760 (KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect DE-627 ger DE-627 rakwb eng 610 ZDB 54.74 bkl Abdelwahab, Ahmed A verfasserin aut Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. Nutzungsrecht: © 2017, World Scientific Publishing Company Enthalten in International journal of image and graphics Singapore [u.a.] : World Scientific, 2001 17(2017), 3 (DE-627)346833507 (DE-600)2078011-4 (DE-576)9346833505 0219-4678 nnns volume:17 year:2017 number:3 http://dx.doi.org/10.1142/S0219467817500176 Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.74 AVZ AR 17 2017 3 |
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10.1142/S0219467817500176 doi PQ20171228 (DE-627)OLC1999748395 (DE-599)GBVOLC1999748395 (PRQ)worldscientific_primary_S02194678175001760 (KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect DE-627 ger DE-627 rakwb eng 610 ZDB 54.74 bkl Abdelwahab, Ahmed A verfasserin aut Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. Nutzungsrecht: © 2017, World Scientific Publishing Company Enthalten in International journal of image and graphics Singapore [u.a.] : World Scientific, 2001 17(2017), 3 (DE-627)346833507 (DE-600)2078011-4 (DE-576)9346833505 0219-4678 nnns volume:17 year:2017 number:3 http://dx.doi.org/10.1142/S0219467817500176 Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.74 AVZ AR 17 2017 3 |
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10.1142/S0219467817500176 doi PQ20171228 (DE-627)OLC1999748395 (DE-599)GBVOLC1999748395 (PRQ)worldscientific_primary_S02194678175001760 (KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect DE-627 ger DE-627 rakwb eng 610 ZDB 54.74 bkl Abdelwahab, Ahmed A verfasserin aut Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. Nutzungsrecht: © 2017, World Scientific Publishing Company Enthalten in International journal of image and graphics Singapore [u.a.] : World Scientific, 2001 17(2017), 3 (DE-627)346833507 (DE-600)2078011-4 (DE-576)9346833505 0219-4678 nnns volume:17 year:2017 number:3 http://dx.doi.org/10.1142/S0219467817500176 Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.74 AVZ AR 17 2017 3 |
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10.1142/S0219467817500176 doi PQ20171228 (DE-627)OLC1999748395 (DE-599)GBVOLC1999748395 (PRQ)worldscientific_primary_S02194678175001760 (KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect DE-627 ger DE-627 rakwb eng 610 ZDB 54.74 bkl Abdelwahab, Ahmed A verfasserin aut Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. Nutzungsrecht: © 2017, World Scientific Publishing Company Enthalten in International journal of image and graphics Singapore [u.a.] : World Scientific, 2001 17(2017), 3 (DE-627)346833507 (DE-600)2078011-4 (DE-576)9346833505 0219-4678 nnns volume:17 year:2017 number:3 http://dx.doi.org/10.1142/S0219467817500176 Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.74 AVZ AR 17 2017 3 |
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| abstract |
Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. |
| abstractGer |
Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. |
| abstract_unstemmed |
Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. Moreover, the code image can be used as a secret key to provide secure communications. |
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Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding |
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http://dx.doi.org/10.1142/S0219467817500176 |
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10.1142/S0219467817500176 |
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2024-07-03T15:19:03.590Z |
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1803571632365633536 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1999748395</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230518003336.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">171228s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1142/S0219467817500176</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20171228</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1999748395</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1999748395</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)worldscientific_primary_S02194678175001760</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0483310420170000017000300000interimagesimilaritybasedfastadaptiveblocksizevect</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ZDB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.74</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Abdelwahab, Ahmed A</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Inter-Image Similarity-Based Fast Adaptive Block Size Vector Quantizer for Image Coding</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Block coding is well known in the digital image coding literature. Vector quantization and transform coding are examples of well-known block coding techniques. Different images have many similar spatial blocks introducing inter-image similarity. The smaller the block size, the higher the inter-image similarity. In this paper, a new block coding algorithm based on inter-image similarity is proposed where it is claimed that any original image can be reconstructed from the blocks of any other image. The proposed algorithm is simply a vector quantization without the need to a codebook design algorithm and using matrix operations-based fast full search algorithm to find the local minimum root-mean-square error distortion measure to find the most similar code block to the input block. The proposed algorithm is applied in both spatial and transform domains with adaptive code block size. In the spatial domain, the encoding process has fidelity as high as 36.07 dB with bit rate of 2.22 bpp, while in the transform domain, the encoded image has good fidelity of 34.94 dB with bit rate as low as 0.72 bpp on the average. 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