Improved Coefficient Recovery and Its Application for Rewritable Data Embedding

JPEG is the most commonly utilized image coding standard for storage and transmission purposes. It achieves a good rate–distortion trade-off, and it has been adopted by many, if not all, handheld devices. However, often information loss occurs due to transmission error or damage to the storage devic...

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Autores principales:	Alan Sii, Simying Ong, KokSheik Wong
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	coefficient recovery segmentation adaptive rewritable DCT Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/e9d220900cd649a0b1d27c3ebe1bed57
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spelling	oai:doaj.org-article:e9d220900cd649a0b1d27c3ebe1bed572021-11-25T18:03:34ZImproved Coefficient Recovery and Its Application for Rewritable Data Embedding10.3390/jimaging71102442313-433Xhttps://doaj.org/article/e9d220900cd649a0b1d27c3ebe1bed572021-11-01T00:00:00Zhttps://www.mdpi.com/2313-433X/7/11/244https://doaj.org/toc/2313-433XJPEG is the most commonly utilized image coding standard for storage and transmission purposes. It achieves a good rate–distortion trade-off, and it has been adopted by many, if not all, handheld devices. However, often information loss occurs due to transmission error or damage to the storage device. To address this problem, various coefficient recovery methods have been proposed in the past, including a divide-and-conquer approach to speed up the recovery process. However, the segmentation technique considered in the existing method operates with the assumption of a bi-modal distribution for the pixel values, but most images do not satisfy this condition. Therefore, in this work, an adaptive method was employed to perform more accurate segmentation, so that the real potential of the previous coefficient recovery methods can be unleashed. In addition, an improved rewritable adaptive data embedding method is also proposed that exploits the recoverability of coefficients. Discrete cosine transformation (DCT) patches and blocks for data hiding are judiciously selected based on the predetermined precision to control the embedding capacity and image distortion. Our results suggest that the adaptive coefficient recovery method is able to improve on the conventional method up to 27% in terms of CPU time, and it also achieved better image quality with most considered images. Furthermore, the proposed rewritable data embedding method is able to embed 20,146 bits into an image of dimensions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>512</mn><mo>×</mo><mn>512</mn></mrow></semantics></math></inline-formula>.Alan SiiSimying OngKokSheik WongMDPI AGarticlecoefficient recoverysegmentationadaptiverewritableDCTPhotographyTR1-1050Computer applications to medicine. Medical informaticsR858-859.7Electronic computers. Computer scienceQA75.5-76.95ENJournal of Imaging, Vol 7, Iss 244, p 244 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	coefficient recovery segmentation adaptive rewritable DCT Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
spellingShingle	coefficient recovery segmentation adaptive rewritable DCT Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95 Alan Sii Simying Ong KokSheik Wong Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
description	JPEG is the most commonly utilized image coding standard for storage and transmission purposes. It achieves a good rate–distortion trade-off, and it has been adopted by many, if not all, handheld devices. However, often information loss occurs due to transmission error or damage to the storage device. To address this problem, various coefficient recovery methods have been proposed in the past, including a divide-and-conquer approach to speed up the recovery process. However, the segmentation technique considered in the existing method operates with the assumption of a bi-modal distribution for the pixel values, but most images do not satisfy this condition. Therefore, in this work, an adaptive method was employed to perform more accurate segmentation, so that the real potential of the previous coefficient recovery methods can be unleashed. In addition, an improved rewritable adaptive data embedding method is also proposed that exploits the recoverability of coefficients. Discrete cosine transformation (DCT) patches and blocks for data hiding are judiciously selected based on the predetermined precision to control the embedding capacity and image distortion. Our results suggest that the adaptive coefficient recovery method is able to improve on the conventional method up to 27% in terms of CPU time, and it also achieved better image quality with most considered images. Furthermore, the proposed rewritable data embedding method is able to embed 20,146 bits into an image of dimensions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>512</mn><mo>×</mo><mn>512</mn></mrow></semantics></math></inline-formula>.
format	article
author	Alan Sii Simying Ong KokSheik Wong
author_facet	Alan Sii Simying Ong KokSheik Wong
author_sort	Alan Sii
title	Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
title_short	Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
title_full	Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
title_fullStr	Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
title_full_unstemmed	Improved Coefficient Recovery and Its Application for Rewritable Data Embedding
title_sort	improved coefficient recovery and its application for rewritable data embedding
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e9d220900cd649a0b1d27c3ebe1bed57
work_keys_str_mv	AT alansii improvedcoefficientrecoveryanditsapplicationforrewritabledataembedding AT simyingong improvedcoefficientrecoveryanditsapplicationforrewritabledataembedding AT koksheikwong improvedcoefficientrecoveryanditsapplicationforrewritabledataembedding
_version_	1718411715134095360

Improved Coefficient Recovery and Its Application for Rewritable Data Embedding

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