VLSI Implementation of Discrete Cosine Transform Approximation Recursive Algorithm
In general, the approximation of Discrete Cosine Transform (DCT) is used to decrease computational complexity without impacting its efficiency in coding. Many of the latest algorithms used in DCT approximation functions have only a smaller DCT length transform of which some are non-orthogonal. For c...
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| Published in: | Journal of physics. Conference series Vol. 1817; no. 1; p. 12017 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Bristol
IOP Publishing
01.03.2021
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | In general, the approximation of Discrete Cosine Transform (DCT) is used to decrease computational complexity without impacting its efficiency in coding. Many of the latest algorithms used in DCT approximation functions have only a smaller DCT length transform of which some are non-orthogonal. For computing DCT orthogonal approximation, a general recursive algorithm is used here, and its length is obtained using DCT pairs of length N/2 of N addition cost in input pre-processing. The recursive sparse matrix has been decomposed by using the vector symmetry from the DCT basis in order to achieve the proposed approximation algorithm that is highly scalable to enforce the highest lengths software and hardware by using a current 8-point approximation to obtain a DCT approximation with two-length power, N>8. |
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| AbstractList | In general, the approximation of Discrete Cosine Transform (DCT) is used to decrease computational complexity without impacting its efficiency in coding. Many of the latest algorithms used in DCT approximation functions have only a smaller DCT length transform of which some are non-orthogonal. For computing DCT orthogonal approximation, a general recursive algorithm is used here, and its length is obtained using DCT pairs of length N/2 of N addition cost in input pre-processing. The recursive sparse matrix has been decomposed by using the vector symmetry from the DCT basis in order to achieve the proposed approximation algorithm that is highly scalable to enforce the highest lengths software and hardware by using a current 8-point approximation to obtain a DCT approximation with two-length power, N>8. |
| Author | Kumar, Naluguru Udaya Raj, E. Fantin Irudaya Ramakrishna, V. Deivakani, M. Kumar, S.V. Sudheer |
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| Cites_doi | 10.1007/s00034-018-0885-6 |
| ContentType | Journal Article |
| Copyright | 2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| DOI | 10.1088/1742-6596/1817/1/012017 |
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| References | Maleika (JPCS_1817_1_012017bib12) 2020; 45 Prakash (JPCS_1817_1_012017bib4) 2012 Al-Azawi (JPCS_1817_1_012017bib11) 2019; 84 Desale (JPCS_1817_1_012017bib3) 2013 Patil (JPCS_1817_1_012017bib1) 2011 Dahiya (JPCS_1817_1_012017bib9) 2019; 38 Aribi (JPCS_1817_1_012017bib5) 2012 Masera (JPCS_1817_1_012017bib10) 2020; 30 Ren (JPCS_1817_1_012017bib6) 2011 Pei (JPCS_1817_1_012017bib7) 2010; 1 Sruthy (JPCS_1817_1_012017bib2) 2013 Huang (JPCS_1817_1_012017bib8) 2014; 45 |
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| SubjectTerms | Algorithms Approximation Discrete cosine transform Integrated circuits Mathematical analysis Matrix methods Physics Sparse matrices |
| Title | VLSI Implementation of Discrete Cosine Transform Approximation Recursive Algorithm |
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