Image and Signal Denoising Methods

Image denoising aims to recover a clean image from noisy observations while preserving structural and edge information. Classical pixel-wise losses, particularly mean squared error (MSE), are effective for noise reduction; however, their local structure may fail to capture nonlocal residual interactions and may cause…

This study investigates the role of memory-weighted (fractional-inspired) regularization in stabilizing training dynamics for deep image denoising. Unlike conventional loss functions that rely solely on instantaneous residuals, the proposed approach introduces a loss-level aggregation mechanism in which past residuals…

Bu çalışma, dijital görüntülerde sıkça karşılaşılan periyodik gürültülerin giderilmesine yönelik derin öğrenme tabanlı hibrit bir yöntem önermektedir. Periyodik gürültü, görüntü kalitesini düşürerek analiz ve yorum süreçlerini güçleştirir. Geleneksel filtreleme yöntemlerinin bu tür gürültüler üzerinde sınırlı başarı s…

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In this study, three global tone mapping operators are built from classical polynomial families to enhance low contrast documentation images, their behaviour fixed in advance by symmetry rather than chosen by taste. Lucas, Faber and Gegenbauer polynomials are generated by a recurrence, a conformal map and an orthogona…

Robust visual perception in extreme low-light environments is a fundamental requirement for autonomous robotic systems operating in unstructured or nighttime conditions. However, conventional enhancement methods often introduce significant computational latency, hindering real-time decision-making and control. This pa…

Thermal imaging technology provides reliable imaging independent of environmental conditions in many critical areas and significantly contributes to object detection and scene interpretation processes in these critical areas. Although these sensors have advantages in terms of low light independence and wide operating…

• CANSEL FIÇICI

Reducing noise in medical imaging is essential to improve quality and diagnostic accuracy. Gaussian noise, common in MRI and X-ray images, reduces clarity and obscures pathological structures. Traditional denoising methods often fail to preserve edge details, leading to the loss of important anatomical information. To…

• AYNUR YONAR

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• MUHAMMED DAVUD