Image and video dehazing using view-based cluster segmentation

التفاصيل البيبلوغرافية
العنوان: Image and video dehazing using view-based cluster segmentation
المؤلفون: Bolun Cai, Xiangmin Xu, Chunmei Qing, Feng Yu
المصدر: VCIP
بيانات النشر: IEEE, 2016.
سنة النشر: 2016
مصطلحات موضوعية: 0209 industrial biotechnology, Computer science, business.industry, media_common.quotation_subject, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Mixture model, Image (mathematics), ComputingMethodologies_PATTERNRECOGNITION, 020901 industrial engineering & automation, Transmission (telecommunications), Sky, Depth map, Distortion, 0202 electrical engineering, electronic engineering, information engineering, Contrast (vision), 020201 artificial intelligence & image processing, Segmentation, Computer vision, Artificial intelligence, business, media_common
الوصف: To avoid distortion in sky regions and make the sky and white objects clear, in this paper we propose a new image and video dehazing method utilizing the view-based cluster segmentation. Firstly, GMM(Gaussian Mixture Model)is utilized to cluster the depth map based on the distant view to estimate the sky region and then the transmission estimation is modified to reduce distortion. Secondly, we present to use GMM based on Color Attenuation Prior to divide a single hazy image into K classifications, so that the atmospheric light estimation is refined to improve global contrast. Finally, online GMM cluster is applied to video dehazing. Extensive experimental results demonstrate that the proposed algorithm can have superior haze removing and color balancing capabilities.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::8fe4692627d496521c9261343a162a64Test
https://doi.org/10.1109/vcip.2016.7805512Test
رقم الانضمام: edsair.doi...........8fe4692627d496521c9261343a162a64
قاعدة البيانات: OpenAIRE