A Neural LUM Smoother
In this paper a design of neural LUM smoother is presented. The LUMsmoother distinguishes by a number of smoothing characteristics done bythe filter parameter. However, the tuning parameter for smoothing isfixed for whole image. The new method realizes adaptive control of thelevel of smoothing by ne...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Spolecnost pro radioelektronicke inzenyrstvi
2000-09-01
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| Series: | Radioengineering |
| Online Access: | http://www.radioeng.cz/fulltexts/2000/00_03_05_07.pdf |
| _version_ | 1818035430011961344 |
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| author | S. Marchevsky R. Lukac |
| author_facet | S. Marchevsky R. Lukac |
| author_sort | S. Marchevsky |
| collection | DOAJ |
| description | In this paper a design of neural LUM smoother is presented. The LUMsmoother distinguishes by a number of smoothing characteristics done bythe filter parameter. However, the tuning parameter for smoothing isfixed for whole image. The new method realizes adaptive control of thelevel of smoothing by neural networks. The well-known and very popularbackpropagation algorithm is used. The analysis of the proposed methodsis evaluated through subjective and objective criteria and comparedwith the traditional LUM smoother. |
| first_indexed | 2024-12-10T06:54:55Z |
| format | Article |
| id | doaj.art-2870b9801cfa4fdfa6c7bf7181b5dc7f |
| institution | Directory Open Access Journal |
| issn | 1210-2512 |
| language | English |
| last_indexed | 2024-12-10T06:54:55Z |
| publishDate | 2000-09-01 |
| publisher | Spolecnost pro radioelektronicke inzenyrstvi |
| record_format | Article |
| series | Radioengineering |
| spelling | doaj.art-2870b9801cfa4fdfa6c7bf7181b5dc7f2022-12-22T01:58:28ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122000-09-019357A Neural LUM SmootherS. MarchevskyR. LukacIn this paper a design of neural LUM smoother is presented. The LUMsmoother distinguishes by a number of smoothing characteristics done bythe filter parameter. However, the tuning parameter for smoothing isfixed for whole image. The new method realizes adaptive control of thelevel of smoothing by neural networks. The well-known and very popularbackpropagation algorithm is used. The analysis of the proposed methodsis evaluated through subjective and objective criteria and comparedwith the traditional LUM smoother.www.radioeng.cz/fulltexts/2000/00_03_05_07.pdf |
| spellingShingle | S. Marchevsky R. Lukac A Neural LUM Smoother Radioengineering |
| title | A Neural LUM Smoother |
| title_full | A Neural LUM Smoother |
| title_fullStr | A Neural LUM Smoother |
| title_full_unstemmed | A Neural LUM Smoother |
| title_short | A Neural LUM Smoother |
| title_sort | neural lum smoother |
| url | http://www.radioeng.cz/fulltexts/2000/00_03_05_07.pdf |
| work_keys_str_mv | AT smarchevsky aneurallumsmoother AT rlukac aneurallumsmoother AT smarchevsky neurallumsmoother AT rlukac neurallumsmoother |