基于多尺度字典的圖像超分辨率重建 - 免費下載
論文資源
文件大小：1221 K
?? 資源詳細信息
?? 溫馨提示：本資源由用戶 fullout 上傳分享，僅供學習交流使用。如有侵權，請聯系我們刪除。
資源簡介
Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
立即下載此資源
提示：下載后請用壓縮軟件解壓，推薦使用 WinRAR 或 7-Zip
資源說明
下載說明
- 下載需消耗 2積分
- 24小時內重復下載不扣分
- 支持斷點續傳
- 資源永久有效
使用說明
- 下載后用解壓軟件解壓
- 推薦 WinRAR 或 7-Zip
- 如有密碼請查看說明
- 解壓后即可使用
積分獲取
- 上傳資源獲得積分
- 每日簽到免費領取
- 邀請好友注冊獎勵
- 查看詳情 →