Assessment of the Segmentation of RGB Remote Sensing Images: A Subjective Approach
| Autor: | Tadas Limba, Mindaugas Kiškis, Edgaras Janusonis, Romualdas Bausys, Giruta Kazakeviciute-Januskeviciene |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Ground truth
Computer science subjective evaluation media_common.quotation_subject Science correlation analysis ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology Image segmentation Data set Human visual system model 0202 electrical engineering electronic engineering information engineering segmentation quality assessment General Earth and Planetary Sciences RGB color model 020201 artificial intelligence & image processing Segmentation Quality (business) Cluster analysis objective quality metrics Remote sensing media_common satellite image segmentation |
| Zdroj: | Remote Sensing Volume 12 Issue 24 Pages: 4152 Remote Sensing, Vol 12, Iss 4152, p 4152 (2020) |
| Popis: | The evaluation of remote sensing imagery segmentation results plays an important role in the further image analysis and decision-making. The search for the optimal segmentation method for a particular data set and the suitability of segmentation results for the use in satellite image classification are examples where the proper image segmentation quality assessment can affect the quality of the final result. There is no extensive research related to the assessment of the segmentation effectiveness of the images. The designed objective quality assessment metrics that can be used to assess the quality of the obtained segmentation results usually take into account the subjective features of the human visual system (HVS). A novel approach is used in the article to estimate the effectiveness of satellite image segmentation by relating and determining the correlation between subjective and objective segmentation quality metrics. Pearson’s and Spearman’s correlation was used for satellite images after applying a k-means++ clustering algorithm based on colour information. Simultaneously, the dataset of the satellite images with ground truth (GT) based on the “DeepGlobe Land Cover Classification Challenge” dataset was constructed for testing three classes of quality metrics for satellite image segmentation. This article belongs to the Special Issue The Quality of Remote Sensing Optical Images from Acquisition to Users This research has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-MIP-19-27. |
| Databáze: | OpenAIRE |
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