自由
发表于 2025-3-21 16:40:02
书目名称Geometrical Multiresolution Adaptive Transforms影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0383660<br><br> <br><br>书目名称Geometrical Multiresolution Adaptive Transforms读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0383660<br><br> <br><br>
DOTE
发表于 2025-3-21 21:25:53
Multismoothletstly to multiple edges. So, the multismoothlet can adapt to edges of different multiplicity, location, scale, orientation, curvature and blur. Additionally, a notion of sliding multismoothlet was introduced. It is the multismoothlet with location and size defined freely within an image. Based on that
精美食品
发表于 2025-3-22 02:49:24
http://reply.papertrans.cn/39/3837/383660/383660_3.png
牵连
发表于 2025-3-22 07:16:56
Image Compressionespectively. Both methods are based on quadtree decomposition of images. Each description of the compression method was followed by the results of numerical experiments. These results were further compared to the known state-of-the-art methods.
BROOK
发表于 2025-3-22 10:50:17
Image Denoisingtations are computed for different values of the penalization factor and the optimal approximation is taken as the result. The algorithm description was followed by the results of numerical experiments. These results were further compared to the known state-of-the-art methods. The proposed algorithm
贝雷帽
发表于 2025-3-22 16:43:29
Edge Detection one is based on sliding multismoothlets. Both methods were compared to the state-of-the-art methods. As follows from the performed experiments, the method based on sliding multismoothlets leads to the best results of edge detection.
贝雷帽
发表于 2025-3-22 17:38:32
http://reply.papertrans.cn/39/3837/383660/383660_7.png
不满分子
发表于 2025-3-22 21:48:47
https://doi.org/10.1007/978-3-319-05011-9Edge Detection; Geometrical Methods; Image Compression; Image Denoising; Multiresolution; Multismoothlets
arbiter
发表于 2025-3-23 03:36:31
http://reply.papertrans.cn/39/3837/383660/383660_9.png
synovial-joint
发表于 2025-3-23 07:58:56
https://doi.org/10.1007/978-1-4612-2358-0espectively. Both methods are based on quadtree decomposition of images. Each description of the compression method was followed by the results of numerical experiments. These results were further compared to the known state-of-the-art methods.