Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 8 No 1 (2024): Volume 8, Issue 1, January 2024 | Pages: 168-177
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 05-02-2024
The image processing field is considered one of the highly sensitive fields for accuracy due to the quality of the processing in view of the visual view of the user and due to the development in modern means of communication and the use of these means in the transfer of images and the impact of these means on several factors, including external, including those related to the quality of the source signal and the impact of the transmitted images by these conditions, digital correction processes have emerged to reach a high quality of the received image. Most of the studies and research on digital image correction have focused on the quality and time required for correction processes, and some have focused on using traditional optimization algorithms to obtain acceptable visual quality, while others have focused on shortening time regardless of quality, and due to the fact that all studies and research that have been viewed were focused on the use of speculative methods and hybrid algorithms to address distortion in images, as all weaknesses were related to time, quality and calculations because the size of the image data is large Very. The research aims to study digital images and then process images, optimization methods, genetic algorithms and accomplish an algorithm with high features. In this paper, the simple genetic algorithm is used in the process of correcting images of the type (.JPG), as this method is characterized by the fact that it includes many of the advantages of the previous methods in addition to additional features that provided quality, accuracy and shortening time in calculations. The paper has been completed in five phases:
The first stage: Providing external protection for the system by entering the password.
Second Stage: Creating the system's database.
Third stage: Create (code book) in a new style based on the size of the file used.
Fourth stage: Building the genetic algorithm for correction.
Fifth stage: Using a mathematical model to add distortion to a clear image, correct it and compare the results.
Image Restoration, Deep Learning, Pre-processing, Post-processing, Performance Evaluation
Ghada Mohammad Tahir KASIM, Zahraa Mazin ALKATTAN, Nadia Maan MOHAMMED, “Hybrid System for Image Restoration” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 1, pp 168-177, January 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.801020
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