Analysis of Improvement of Noisy Multichannel Image Controlled Pixel-by-Pixel Classification by Post-Classification Processing
| Autor: | Vladimir V. Lukin, Irina Vasilyeva, Galina Proskura |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Spatial filter
Pixel Noise (signal processing) Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Image segmentation Image (mathematics) Support vector machine symbols.namesake ComputingMethodologies_PATTERNRECOGNITION Additive white Gaussian noise Computer Science::Computer Vision and Pattern Recognition symbols Artificial intelligence Pixel classification business |
| Zdroj: | 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET). |
| DOI: | 10.1109/tcset49122.2020.235488 |
| Popis: | A post-classification processing technique for noisy multichannel image that includes the method of local spatial filtering of segmented images in pseudo colors and multilayer classification algorithm is proposed. The post-classification processing effectiveness is verified for satellite image degraded by additive white Gaussian noise. It is demonstrated that the presence of noise in remote sensing data complicates the recognition task in pixel-by-pixel classification leading to a large number of arising errors. It is shown that post-classification processing can significantly increase overall probability of correct recognition of objects in noisy images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|