Numerical Optimization and Hybrid Algorithms for Image Processing and Encryption Using Heat Equation.
This study investigates developing and optimizing hybrid algorithms for image processing and encryption using numerical optimization techniques based on heat diffusion methods. Using finite difference methods, we show the application to different types of images, which will be converted into arrays...
| Publicado en: | Journal of Basrah Researches (Sciences) Vol. 51; no. 1; pp. 43 - 59 |
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| Formato: | Artículo |
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Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR)
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=187442045&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 187442045 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 18172695 GYGY jtl: Journal of Basrah Researches (Sciences) issn: 18172695 maglogo: N pubinfo: dt: 2025 vid: 51 iid: 1 pid: 25427 pub: Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) artinfo: ui: 187442045 10.56714/bjrs.51.1.4 ppf: 43 ppct: 16 formats: tig: atl: Numerical Optimization and Hybrid Algorithms for Image Processing and Encryption Using Heat Equation. aug: au: Ahmed, Zainab Hassan affil: Department of Mathematics, College of Science, Tikrit University, Tikrit 34001, Iraq. su: Finite difference method Finite differences Image encryption Image processing Heat equation sug: subj: Finite difference method Finite differences Image encryption Image processing Heat equation keyword: Finite Differences Heat Diffusion Hybrid Algorithm Image Processing Numerical Optimization الأمثلية العددية الخوارزميات الهجينة الفروقات المنتهية معادلة الحرارة معالجة صورية ab: This study investigates developing and optimizing hybrid algorithms for image processing and encryption using numerical optimization techniques based on heat diffusion methods. Using finite difference methods, we show the application to different types of images, which will be converted into arrays and treated as coefficients in the computational process. The paper aims to enhance image quality through algorithmic optimization and hybridization strategies. Experiments in one and two dimensions are conducted using both explicit and implicit methods to evaluate the impact of these techniques on image processing. The performance of the proposed approach is analyzed using statistical metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Maximum Difference (MD), and additional quality assessment parameters. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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