Adaptive Enhancement Algorithm of High-Resolution Satellite Image Based on Feature Fusion. (11th January 2022)
- Record Type:
- Journal Article
- Title:
- Adaptive Enhancement Algorithm of High-Resolution Satellite Image Based on Feature Fusion. (11th January 2022)
- Main Title:
- Adaptive Enhancement Algorithm of High-Resolution Satellite Image Based on Feature Fusion
- Authors:
- Wang, Ruizhe
Xiao, Wang - Other Names:
- Jan Naeem Academic Editor.
- Abstract:
- Abstract : Since the traditional adaptive enhancement algorithm of high-resolution satellite images has the problems of poor enhancement effect and long enhancement time, an adaptive enhancement algorithm of high-resolution satellite images based on feature fusion is proposed. The noise removal and quality enhancement areas of high-resolution satellite images are determined by collecting a priori information. On this basis, the histogram is used to equalize the high-resolution satellite images, and the local texture features of the images are extracted in combination with the local variance theory. According to the extracted features, the illumination components are estimated by Gaussian low-pass filtering. The illumination components are fused to complete the adaptive enhancement of high-resolution satellite images. Simulation results show that the proposed algorithm has a better adaptive enhancement effect, higher image definition, and shorter enhancement time.
- Is Part Of:
- Journal of mathematics. Volume 2022(2022)
- Journal:
- Journal of mathematics
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01-11
- Subjects:
- Mathematics -- Periodicals
Mathematics
Periodicals
510 - Journal URLs:
- https://www.hindawi.com/journals/jmath/ ↗
http://bibpurl.oclc.org/web/74492 ↗
http://search.ebscohost.com/direct.asp?db=a9h&jid=%22FV7F%22&scope=site ↗ - DOI:
- 10.1155/2022/1029247 ↗
- Languages:
- English
- ISSNs:
- 2314-4629
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 20717.xml