TY  - BOOK
AU  - Farhadifard, Fahimeh
PY  - 2017
DA  - 2017//
TI  - Underwater image restoration: super-resolution and deblurring via sparse representation and denoising by means of marine snow removal
PB  - Universität Rostock
CY  - Rostock
AB  - Underwater imaging has been widely used as a tool in many fields, however, a major issue is the quality of the resulting images/videos. Due to the light's interaction with water and its constituents, the acquired underwater images/videos often suffer from a significant amount of scatter (blur, haze) and noise. In the light of these issues, this thesis considers problems of low-resolution, blurred and noisy underwater images and proposes several approaches to improve the quality of such images/video frames. Quantitative and qualitative experiments validate the success of proposed algorithms.<eng>
UR  - http://rosdok.uni-rostock.de/resolve/urn/urn:nbn:de:gbv:28-diss2018-0082-2
UR  - https://nbn-resolving.org/urn:nbn:de:gbv:28-diss2018-0082-2
UR  - https://d-nb.info/129365261X/34
UR  - https://doi.org/10.18453/rosdok_id00002088
DO  - 10.18453/rosdok_id00002088
LA  - English
N1  - vorgelegt von Fahimeh Farhadifard
ID  - 1025383222
ER  -