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الرئيسية > Cuckoo Inspired Fast Search Al...>الوصف

Cuckoo Inspired Fast Search Algorithm For Fractal Image Encoding

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Ismail, B. Mohammed (Author)
مؤلفين آخرين: Reddy, B. Eswara (Co-Author), Reddy, T. Bhaskara (Co-Author)
المجلد/العدد: مج30, ع4
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2018
الصفحات: 462 - 469
DOI: 10.33948/0584-030-004-003
ISSN: 1319-1578
رقم MD: 974468
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
الخوارزميات | الخوارزميات الجينية | تشفير الصور
كلمات المؤلف المفتاحية:
Fractal | PSNR | Cuckoo Search | PSO | Genetic Algorithm | MSE
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المستخلص: The search time and significant loss in compression are the significant constraints of the traditional fractal image compression. Hence, the contemporary research contributions are aimed to discover optimal solutions to speed up the search speed with minimal loss of image significance at compression. Majority of the existing contributions achieve the search speed at the cost of decoded image quality and vice versa. In regard to this, we proposed a cuckoo inspired fast search (CIFS) technique for fractal image compression. Unlike the many of traditional models, which depend on 3 level wavelet classification, this proposed CIFS is using ordered vector of range blocks by their similarity and ordered vector of range blocks by their coordinate distance. The experimental study evinced that the proposed model is scalable and robust compared to PSO and GA based models found in contemporary literature. The significant reduction in mean square error calculations is also observed, since the only four transformations of the dihedral group are sufficient to compare for similarity here in this proposed CIFS.
ISSN: 1319-1578

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