Proposing a New Image Watermarking Method Using Shearlet Transform and Whale Optimization Algorithm
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 277
This Paper With 11 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJE-34-4_010
تاریخ نمایه سازی: 6 اردیبهشت 1400
Abstract:
Digital images watermarking is a method for data hiding that ensures the security of multimedia data. In these ways, a watermark can be a digital image or data stored within digital content. The Shearlet transform, a multi-resolution and multi-directional conversion, can be used for watermarking in digital images. Due to its superior features, this conversion can increase the efficiency of applications such as watermarking of images. In this paper, Shearlet and SVD transforms are used with the Whale optimization algorithm to obtain the most appropriate scaling factor in the watermark extraction step after applying different types of image processing attacks. Shearlet Transform has more transparency than traditional converts. The SVD transform also increases the robustness of watermarking operations. The results of different experiments show that the new method presented in this paper, in terms of robustness and imperceptibility compared to the methods tested, performs better than most image processing attacks.
Keywords:
Authors
M. Saadati
Department of Computer Engineering, Artificial Intelligence, South Tehran Branch, Islamic Azad University, Tehran, Iran
J. Vahidi
Department of Applied Mathematics, Iran University of Science and Technology, Tehran, Iran
V. Seydi
Department of Computer Engineering, Artificial Intelligence, South Tehran Branch, Islamic Azad University, Tehran, Iran
P. Sheikholharam Mashhadi
Department of Computer Engineering, Artificial Intelligence, South Tehran Branch, Islamic Azad University, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :