International Conference on Digital Technologies, Optics, and Materials Science · August 14, 2026

Noise reduction and quality assessment in images using quantum computing based on artificial intelligence agents

D.T. Muhamediyeva, Narzillo Mamatov, U. N. Ganiyev, B. N. Samijonov, G. Usnatdinova

Abstract

This article investigates the automation of image processing processes based on artificial intelligence agents and agentic artificial intelligence approaches. The research developed artificial noise addition to digital images, initial filtering using median filter, and an improved noise reduction method based on quantum computing elements. The software model was implemented using Python programming environment, Open Source Computer Vision (OpenCV library, and quantum computing platform. Computational processes affecting image pixel values were modeled through quantum circuits, and results were evaluated based on natural image quality indicators. Image quality was analyzed using Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE), Natural Image Quality Evaluator (NIQE), and Blind Image Quality Index (BIQI) metrics, demonstrating the effectiveness of quantum-based filtering method compared to simple median filtering. Additionally, the article scientifically illuminates the differences between artificial intelligence agents and agentic artificial intelligence through image processing examples. The proposed model holds significant importance in creating intelligent automated image processing systems.

Image and Signal Denoising MethodsImage and Video Quality AssessmentImage Enhancement Techniquesimage denoisingquantum computingAI agents

Noise reduction and quality assessment in images using quantum computing based on artificial intelligence agents

Abstract

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