Sis Kaldırma Algoritmalarına Genel Bir Bakış

Year 2023, Volume: 6 Issue: 1, 46 - 60, 30.06.2023

Bahadır Arabalı , Kemal Fidanboylu

Abstract

Sisli ve puslu havalarda çekilen görüntüler gerçekliğini kaybetmektedir. Bu görüntülerden sisin kaldırılmasına, sis kaldırma (dehazing, defogging, fog removal) denilmektedir. Sis kaldırma işleminden sonra elde edilen imgenin içindeki görünürlük artmaktadır. Sis kaldırma işlemi, imgenin yakalandığı zamana (gece, gündüz), imge içerisindeki sisin yoğunluğuna, imge içerisindeki ışık kaynağına vb. etkenlere doğrudan bağlıdır. Literatürde, birçok araştırmacı sis kaldırma problemini çözmek için farklı algoritmalar kullandılar. Bu bildiride, literatürde yaygın olarak kullanılan sis kaldırma algortimaları incelenecektir. Bu incelemeler yapılırken, farklı algortimalardan elde edilen sonuçlar birbirleri ile farklı görüntü kalitesi ölçütleri aracılığı ile karşılaştırılacak ve algoritmaların güçlü ve zayıf yönleri ortaya çıkarılacaktır. İncelemelerde, hem gerçek sis içeren görüntüler, hem de yapay olarak sis eklenmiş görüntüler içeren O-HAZE veri kümesinden örnekler kullanılacaktır

Keywords

Görüntü İşleme, Sis Kaldırma, Görüntü Onarma, Kontrast İyileştirme, Dark Channel Prior Algoritması

An Overview of Fog Removal Algorithms

Abstract

Images taken in foggy and hazy weather conditions lose their authenticity. Removing the fog from these images is called fog removal (dehazing, defogging, fog removal). Visibility in the image obtained after the fog removal process increases. The fog removal process depends on the time the image was captured (day, night), the density of the fog in the image, the light source in the image, etc. In the literature, many researchers have used different algorithms to solve the fog removal problem. In this paper, fog removal algorithms, which are widely used in the literature, will be examined. While these examinations are being made, the results obtained from different algorithms will be compared with each other through different image quality criteria and the strengths and weaknesses of the algorithms will be revealed. Samples from the O-HAZE dataset will be used in the reviews, which contain both images with real fog and images with artificial fog.

Keywords

Image Processing, Fog Removal, Image Restoration, Contrast Enhancement, Dark Channel Prior Algorithm

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