Düşük ışıklı mağara görsellerinin iyileştirilmesinde farklı Retineks yöntemlerinin performans karşılaştırması

Year 2025, Volume: 14 Issue: 4, 1625 - 1637, 15.10.2025

Bilgin Yazlık , Egemen Nazife Yazlık

Abstract

Mağaralar dünyanın içine açılan, çoğunlukla ya tamamen ışıksız ya da çok az ışık alan mekanlardır. Mağaraların içinde çekilen fotoğraflar genellikle çok düşük ışık koşullarına maruz kalır ve görsel kaliteleri olumsuz etkilenir. Bu çalışmada, mağarada çekilen görüntülerin kalitesini iyileştirmek için güncel Retinex tabanlı görüntü iyileştirme yöntemleri kullanılmıştır. İyileştirilen görüntüler hem nicel hem de nitel olarak değerlendirilmiştir. Nicel analiz için 82 adet düşük ışık görüntüsünden oluşan bir mağara görüntü veri seti kullanılmıştır. Nitel analiz için tüm yöntemlerin iyileştirme sonuçları, veri setinden seçilen üç örnek görüntü ile görsel olarak karşılaştırılmıştır. On bir farklı görüntü kalitesi değerlendirme yöntemi nicel analiz için uygulanmıştır. Çalışmanın sonuçları, Retinex tabanlı yöntemlerin düşük ışıklı mağara görüntülerini iyileştirmede başarılı olduğunu göstermektedir. Genel görüntü iyileştirme ve yapısal tutarlılık gerektiren uygulamalar için BIMEF önerilirken, yüksek dinamik aralık ve detay korunması gereken uygulamalarda MSRETINEX ve LIME tercih edilebilir. Gürültü azaltma ve nesnel kalite değerlendirme metriklerinin ön planda olduğu durumlarda SRIE avantaj sağlamaktadır.

Keywords

Retineks , mağara , görüntü iyileştirme , performans , kıyaslama

Performance comparison of different Retinex methods on enhancement of low light cave images

Abstract

Caves are spaces that open into the earth and are often either completely dark or receive very little light. Photographs taken inside caves are usually subject to extremely low light conditions and image quality is negatively affected. In this study, state-of-the-art Retinex-based image enhancement methods are used to enhance the quality of images taken in the cave. Enhanced images are evaluated both quantitatively and qualitatively. A cave image dataset consisting of 82 low-light images is used for quantitative analysis. The enhanced results from all methods are visually compared using three sample images from the dataset for qualitative analysis. Eleven different image quality assessment methods are applied for quantitative analysis. The results of the study show that Retinex-based methods are successful in the enhancement of low-light cave images. While BIMEF is recommended for applications requiring general image enhancement and structural consistency, MSRETINEX and LIME can be preferred in applications requiring high dynamic range and detail preservation. In cases where noise reduction and objective quality assessment metrics are at the forefront, SRIE provides advantages.

Keywords

Retinex , cave , image enhancement , performance , compare

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