| DC Field | Value | Language |
|---|
| dc.contributor.author | Jing Wang | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2026-04-27T08:30:40Z | - |
| dc.date.available | 2026-04-27T08:30:40Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | Jing Wang. Development of mathematical tools for image restoration with distorted data / Jing Wang // Технические средства защиты информации : материалы ХXIV Международной научно-технической конференции, Минск, 8 апреля 2026 года / Белорусский государственный университет информатики и радиоэлектроники [и др.] ; редкол.: О. В. Бойправ [и др.]. – Минск, 2026. – С. 124–126. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/63397 | - |
| dc.description.abstract | This paper addresses image restoration in the presence of Gaussian noise, salt and pepper noise, occlusion and blur. A review of mathematical methods-from Fourier filters and statistical hypothesis testing to regression trees-is presented. The research aims to develop a unified framework for image quality assessment integrating statistical rigor with computational techniques. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | images | en_US |
| dc.subject | Kolmogorov-Smirnov test | en_US |
| dc.subject | Gaussian noise | en_US |
| dc.subject | occlusion | en_US |
| dc.subject | quality assessment | en_US |
| dc.title | Development of mathematical tools for image restoration with distorted data | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | ТСЗИ 2026
|
