dor_id: 4110203

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590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation

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336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/758/722

100.1.#.a: Ishtiaq, Muhammad; Jaffar, Arfan

524.#.#.a: Ishtiaq, Muhammad, et al. (2017). A novel Diamond-Mean predictor for reversible watermarking of images. Journal of Applied Research and Technology; Vol. 15 Núm. 6. Recuperado de https://repositorio.unam.mx/contenidos/4110203

245.1.0.a: A novel Diamond-Mean predictor for reversible watermarking of images

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2017

264.#.1.c: 2019-07-23

653.#.#.a: Prediction; Error-expansion; Reversible watermarking; MED; GAP; D-Mean

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/758

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041.#.7.h: eng

520.3.#.a: Reversible watermarking (RW) is the art of embedding secret information in the host image such that after extraction of hidden information, original image is also restored from the watermarked image. Prediction error expansion (PEE) is state of the art technique for RW. Performance of PEE methods depends on the predictor’s ability to accurately estimate image pixels. In this paper, a novel Diamond-Mean (D-Mean) prediction mechanism is presented. The D-Mean predictor uses only D-4 neighbors of a pixel, i.e. pixels located at {east, west, north, south}. In the estimation process, apart from edge presence, its orientation and sensitivity is also taken into account. In experimental evaluations, the D-Mean predictor outperforms currently in use MED (median edge detector) and GAP (gradient adjusted predictor) predictors. For, standard test images of Lena, Airplane, Barbara and Baboon, an average improvement of 51.79 for mean squared PE and an average improvement of 0.4 for error-entropy than MED/GAP are observed. Payload vs imperceptibility comparison of the method shows promising results.

773.1.#.t: Journal of Applied Research and Technology; Vol. 15 Núm. 6

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.1016/j.jart.2017.06.001

harvesting_date: 2023-11-08 13:10:00.0

856.#.0.q: application/pdf

file_creation_date: 2018-01-10 16:41:20.0

file_modification_date: 2018-01-10 11:18:50.0

file_creator: Muhammad Ishtiaq

file_name: dd48b9e62535ae77026448e8babaa344a5363bb427a590d618c9024fd74152a9.pdf

file_pages_number: 9

file_format_version: application/pdf; version=1.7

file_size: 1684011

last_modified: 2024-03-19 14:00:00

license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es

license_type: by-nc-sa

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Artículo

A novel Diamond-Mean predictor for reversible watermarking of images

Ishtiaq, Muhammad; Jaffar, Arfan

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Ishtiaq, Muhammad, et al. (2017). A novel Diamond-Mean predictor for reversible watermarking of images. Journal of Applied Research and Technology; Vol. 15 Núm. 6. Recuperado de https://repositorio.unam.mx/contenidos/4110203

Descripción del recurso

Autor(es)
Ishtiaq, Muhammad; Jaffar, Arfan
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
A novel Diamond-Mean predictor for reversible watermarking of images
Fecha
2019-07-23
Resumen
Reversible watermarking (RW) is the art of embedding secret information in the host image such that after extraction of hidden information, original image is also restored from the watermarked image. Prediction error expansion (PEE) is state of the art technique for RW. Performance of PEE methods depends on the predictor’s ability to accurately estimate image pixels. In this paper, a novel Diamond-Mean (D-Mean) prediction mechanism is presented. The D-Mean predictor uses only D-4 neighbors of a pixel, i.e. pixels located at {east, west, north, south}. In the estimation process, apart from edge presence, its orientation and sensitivity is also taken into account. In experimental evaluations, the D-Mean predictor outperforms currently in use MED (median edge detector) and GAP (gradient adjusted predictor) predictors. For, standard test images of Lena, Airplane, Barbara and Baboon, an average improvement of 51.79 for mean squared PE and an average improvement of 0.4 for error-entropy than MED/GAP are observed. Payload vs imperceptibility comparison of the method shows promising results.
Tema
Prediction; Error-expansion; Reversible watermarking; MED; GAP; D-Mean
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

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