Water Classification Based on Underwater Monocular Image

2021 ◽  
Author(s):  
Everson Fagundes de Toledo ◽  
Edwilson Silva Vaz ◽  
Paulo L. J. Drews
Keyword(s):  
Water Classification ◽  
Monocular Image

scholarly journals An Overview on Water Quality Trending for Lake Water Classification in Malaysia

2018 ◽  
Vol 7 (3.23) ◽  
pp. 5
Author(s):  
Muhammad Muzzammil Shahabudin ◽  
Sabariah Musa
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Lake Water ◽  
Quality Index ◽  
Water Quality Assessment ◽  
Lake Water Quality ◽  
Water Classification ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Quality Assessments

Lake water is important to all life and surroundings with multiples benefits and forms either in natural or man-made conditions. One of the most well-known tools for assessing the water quality is Water Quality Index (WQI) and widely used including Malaysia. Lake water quality should be represented in lucid way like other surface water regarding to the WQI standards for water quality assessment on lakes. This paper aims to review on lake water quality classification and its uses based on WQI standards in Malaysia. In this review, the uses of WQI for assessing the lake water and functioned of lakes are discussed. Results on pH from 5.0 to 9.2, BOD in mg/l from 0 to 180, COD in mg/l from 5 to 150, SS in mg/l from o to 1800, DO in mg/l from 0 to 8 and AN in mg/l N from -1 to 26. Variety of numbers is due to different loading of pollutions and location. With used of WQI on lake water quality assessments, further action can be taken for the uses on water resources by maintaining the quality. It also will broaden the uses of lake water as alternative of water resources in Malaysia.  

scholarly journals Method for Shape Recovery from Monocular Image Considering Shading.

1996 ◽  
Vol 62 (594) ◽  
pp. 635-643
Author(s):  
Takeshi SETA ◽  
Tetsuji SAITO ◽  
Ryoichi TAKAHASHI
Keyword(s):  
Shape Recovery ◽  
Monocular Image

scholarly journals Compiling a new glacier inventory for southeastern Qinghai–Tibet Plateau from Landsat and PALSAR data

2016 ◽  
Vol 62 (233) ◽  
pp. 579-592 ◽  
Author(s):  
LINGHONG KE ◽  
XIAOLI DING ◽  
LEI ZHANG ◽  
JUN HU ◽  
C. K. SHUM ◽  
...  
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Tibet Plateau ◽  
Landsat 8 ◽  
Glacier Change ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Radar Images ◽  
Water Classification ◽  
Multi Temporal ◽  
Classification Information

ABSTRACTGlacier change has been recognized as an important climate variable due to its sensitive response to climate change. Although there are a large number of glaciers distributed over the southeastern Qinghai–Tibetan Plateau, the region is poorly represented in glacier databases due to seasonal snow cover and frequent cloud cover. Here, we present an improved glacier inventory for this region by combining Landsat observations acquired over 2011–13 (Landsat 8/OLI and Landsat TM/ETM+), coherence images from Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar images and the Shuttle Radar Topography Mission (SRTM) DEM. We present a semi-automated scheme for integrating observations from multi-temporal Landsat scenes to mitigate cloud obscuration. Further, the clean-ice observations, together with coherence information, slope constraints, vegetation cover and water classification information extracted from the Landsat scenes, are integrated to determine the debris-covered glacier area. After manual editing, we derive a new glacier inventory containing 6892 glaciers >0.02 km2, covering a total area of 6566 ± 197 km2. This new glacier inventory indicates gross overestimation in glacier area (over 30%) in previously published glacier inventories, and reveals various spatial characteristics of glaciers in the region. Our inventory can be used as a baseline dataset for future studies including glacier change assessment.

Multi-person 3D Pose Estimation from Monocular Image Sequences

2019 ◽  
pp. 15-24
Author(s):  
Ran Li ◽  
Nayun Xu ◽  
Xutong Lu ◽  
Yucheng Xing ◽  
Haohua Zhao ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Image Sequences ◽  
3D Pose Estimation ◽  
Monocular Image

scholarly journals Operational algorithm for ice/water classification on dual-polarized RADARSAT-2 images

2016 ◽  
Author(s):  
Natalia Zakhvatkina ◽  
Anton Korosov ◽  
Stefan Muckenhuber ◽  
Stein Sandven ◽  
Mohamed Babiker
Keyword(s):  
Sea Ice ◽  
Texture Features ◽  
Open Water ◽  
Support Vector ◽  
Technical Problems ◽  
Additional Information ◽  
Franz Josef Land ◽  
Water Classification ◽  
Dual Polarized ◽  
Supervised Image Classification

Abstract. Synthetic aperture radar (SAR) data from RADARSAT-2 (RS2) taken in dual-polarization mode provide additional information for discriminating sea ice and open water compared to single-polarization data. We have developed a fully automatic algorithm to distinguish between open water (rough/calm) and sea ice based on dual-polarized RS2 SAR images. Several technical problems inherent in RS2 data were solved on the pre-processing stage including thermal noise reduction in HV-polarization channel and correction of angular backscatter dependency on HH-polarization. Texture features are used as additional information for supervised image classification based on Support Vector Machines (SVM) approach. The main regions of interest are the ice-covered seas between Greenland and Franz Josef Land. The algorithm has been trained using 24 RS2 scenes acquired during winter months in 2011 and 2012, and validated against the manually derived ice chart product from the Norwegian Meteorological Institute. Between 2013 and 2015, 2705 RS2 scenes have been utilised for validation and the average classification accuracy has been found to be 91 ± 4 %.

Sign in / Sign up

Export Citation Format

Share Document