Image Enhancement Techniques

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Remote sensing image captioning (RSIC) requires joint understanding of complex visual scenes and the generation of coherent natural-language descriptions. In this study, we investigate the influence of different visual representation models on caption generation performance inside a unified transformer-based captionin…

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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…

Nowadays digital environment, the rapid duplication and unauthorized use of color images shared online have led to increasing concerns regarding copyright infringement and data security. Therefore, the development of effective and robust methods for protecting digital content has become critically important. In this s…

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Gece araç kullanırken karşıdan gelen araç farlarının ışıkları sürücülerin görüşünü ciddi şekilde kısıtlayarak yol güvenliğini tehlikeye atmaktadır. Çalışmada, bu soruna çözüm olarak parlak bölgeleri azaltırken yol detaylarının netliğini koruyan görüntü iyileştirme yöntemleri geliştirilmiştir. Çalışmada, Ortalamaya Ada…

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Low-light images often suffer from low contrast, noise pollution, and loss of detail information, significantly degrading the performance of subsequent image processing tasks. Existing Transformer-based image enhancement methods are characterized by large model parameters, high computational complexity, and poor real-…

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…

To facilitate ease of data compilation across diverse populations for training models to synthesize clinical contrast-weighted images from magnetic resonance fingerprinting. We leverage a semi-supervised training framework using highly accelerated acquisitions of the target contrasts used as ground truths. We utilize…

Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we introduce GWFP (Global Wildfire Prevention Dataset), a large-scale, open-source dataset of wildfire images and videos designed to support early fire and smoke detection rese…