The application of one-bit optimized tensor completion method in the recovery of distorted digital images
(کاربرد روش تکمیل تنسوری بهینهسازی شده تک بیتی در بازیافت تصاویر دیجیتالی مخدوش)

Title The application of one-bit optimized tensor completion method in the recovery of distorted digital images
Title Original کاربرد روش تکمیل تنسوری بهینهسازی شده تک بیتی در بازیافت تصاویر دیجیتالی مخدوش
Author Mohsen Shahrezaei, Alireza Shojaeifard, Hamidreza Yazdani
Author Original محسن شاهرضایی علیرضا شجاعی فرد حمیدرضا یزدانی
Publication Place Shahid Chamran University of Havz - Shahid Chamran University of Havz
Subject recovery of digital images; Tensor; high order tensor; Tensorial completion
Type Periodical
Language Arabic
Digital Yes
Manuscript No
Library: Purdue University Libraries
Library Asset ID ISSN: 2251-8088, EISSN: 2645-6141, DOI: 10.22055/jamm.2021.38887.1971
Record ID cdi_doaj_primary_oai_doaj_org_article_7986add877f34686a453b5e3b7bd6b01
Notes High-order tensorial structural data are used in many imaging scenarios such as hyperspectral imaging and color videos. Retrieving a tensor from an incomplete set of elements, which is called tensor completion, has many applications in fields such as digital image processing and compression. In tensorial completion, in addition to the incompleteness of the observed data, another problem is the quantification of the verses. Quantization is an important step for the transmission and storage of high-dimensional data in order to reduce the need for storage and save energy. Here, a new method for recovering low-rank tensors from a small number of binary (single-bit) measurements is presented. The single-bit tensor completion method relies on the application of tensor completion in matrixed versions with binary data in the contextual tensor of the data. Experimental results in hyperspectral images show that direct operation with binary measurement, instead of their true values, leads to less recovery error. Here, a given third-order tensor is recovered with binary terms. In practice, we open the tensor as a ternary hypermatrix and apply the quantified tensorial completion algorithm to all models of the said tensor matrix. The data space here is hyperspectral satellite images with the aim of recovering distorted images.
Atıf Kaynağı DOAJ Open Access Full Text
Bir Parçası Olduğu Mudil/sāzī-i pīshraftah- riyāz̤ī, 1400-10, Vol.11 (4), p.686-698
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The application of one-bit optimized tensor completion method in the recovery of distorted digital images

(کاربرد روش تکمیل تنسوری بهینهسازی شده تک بیتی در بازیافت تصاویر دیجیتالی مخدوش)
Author Mohsen Shahrezaei, Alireza Shojaeifard, Hamidreza Yazdani
Author Original محسن شاهرضایی علیرضا شجاعی فرد حمیدرضا یزدانی
Publication Place Shahid Chamran University of Havz - Shahid Chamran University of Havz
Subject recovery of digital images; Tensor; high order tensor; Tensorial completion
Type Periodical
Language Arabic
Digital Yes
Manuscript No
Library Purdue University Libraries
Library Asset ID ISSN: 2251-8088, EISSN: 2645-6141, DOI: 10.22055/jamm.2021.38887.1971
Record ID cdi_doaj_primary_oai_doaj_org_article_7986add877f34686a453b5e3b7bd6b01
Notes High-order tensorial structural data are used in many imaging scenarios such as hyperspectral imaging and color videos. Retrieving a tensor from an incomplete set of elements, which is called tensor completion, has many applications in fields such as digital image processing and compression. In tensorial completion, in addition to the incompleteness of the observed data, another problem is the quantification of the verses. Quantization is an important step for the transmission and storage of high-dimensional data in order to reduce the need for storage and save energy. Here, a new method for recovering low-rank tensors from a small number of binary (single-bit) measurements is presented. The single-bit tensor completion method relies on the application of tensor completion in matrixed versions with binary data in the contextual tensor of the data. Experimental results in hyperspectral images show that direct operation with binary measurement, instead of their true values, leads to less recovery error. Here, a given third-order tensor is recovered with binary terms. In practice, we open the tensor as a ternary hypermatrix and apply the quantified tensorial completion algorithm to all models of the said tensor matrix. The data space here is hyperspectral satellite images with the aim of recovering distorted images.
Atıf Kaynağı DOAJ Open Access Full Text
Bir Parçası Olduğu Mudil/sāzī-i pīshraftah- riyāz̤ī, 1400-10, Vol.11 (4), p.686-698
Purdue University Libraries - Ottoman library catalog search
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