A statistical framework for degraded underwater video generation
A statistical framework for degraded underwater video generation
Dosyalar
Tarih
2023
Yazarlar
Şatak, Serkan
Süreli Yayın başlığı
Süreli Yayın ISSN
Cilt Başlığı
Yayınevi
Graduate School
Özet
Computer vision in the underwater medium presents unique challenges due to the
distinct properties and conditions encountered beneath the water’s surface. Underwater
environments are characterized by limited visibility, color distortion, scattering of
light, and various water conditions such as turbidity and currents. These factors
severely impact the performance of traditional computer vision algorithms designed
for terrestrial images, leading to significant difficulties in underwater image and video
analysis.
One of the primary hardships in underwater computer vision is the degradation of
image quality caused by the attenuation of light. As light travels through water, it
is absorbed and scattered, resulting in reduced contrast, loss of details, and color
distortion. These effects make object detection, recognition, and tracking challenging
tasks. Additionally, the scattering of light causes blurring and reduces the sharpness of
underwater images, further impeding accurate analysis.
Another significant hurdle is the lack of reliable, in-depth information. Estimating
depth in underwater scenes is complex due to the varying water conditions and the
absence of well-defined visual cues. This limitation poses challenges for tasks such as
3D reconstruction, scene understanding, and object localization.
Açıklama
Thesis (M.Sc.) -- İstanbul Technical University, Graduate School, 2023
Anahtar kelimeler
underwater,
underwater environments,
underwater image,
underwater image video