FSR vs DLSS - 3C
By Skylar DavisLinda
at 2021-07-02T15:59
at 2021-07-02T15:59
Table of Contents
AMD 的 FSR (FidelityFX Super Resolution),影像放大技術。原理是很清楚的
用2d像素畫解釋比較清楚
https://i.imgur.com/ExGPDuU.png
用AA找出邊線,銳利化,然後放大。這類的演算法其實蠻多的。FSR的重點是,開源,容易整合,效果不錯。100分的效果可以得80分。
(T)AA(U) 其實是一樣的的原理,但多了(Temporal)的取樣,換句話說,取樣比單純AA多,效果當然會比FSR好,但TAA不容易實做。這類型的效果可以得85分。
DLSS是真的運用AI來突破目前演算法的限制。
再用2d像素畫來大概解釋一下
https://i.imgur.com/sNFIsv7.png
有很多的邊線演算法,但每一個演算法都有優點, 缺點,如果能在同一個畫面上,不同物件上選擇適合的演算法,那不是更好嗎?
DLSS就是這樣的概念,DL學習在同樣的畫面,但不同物件上找到最佳的放大演算法。當然效果是90分以上。
其實FSR有80分,又容易應用,是很好的事情。但明示或暗示可以跟DLSS比,真的是XX比圈圈。
--
用2d像素畫解釋比較清楚
https://i.imgur.com/ExGPDuU.png
用AA找出邊線,銳利化,然後放大。這類的演算法其實蠻多的。FSR的重點是,開源,容易整合,效果不錯。100分的效果可以得80分。
(T)AA(U) 其實是一樣的的原理,但多了(Temporal)的取樣,換句話說,取樣比單純AA多,效果當然會比FSR好,但TAA不容易實做。這類型的效果可以得85分。
DLSS是真的運用AI來突破目前演算法的限制。
再用2d像素畫來大概解釋一下
https://i.imgur.com/sNFIsv7.png
有很多的邊線演算法,但每一個演算法都有優點, 缺點,如果能在同一個畫面上,不同物件上選擇適合的演算法,那不是更好嗎?
DLSS就是這樣的概念,DL學習在同樣的畫面,但不同物件上找到最佳的放大演算法。當然效果是90分以上。
其實FSR有80分,又容易應用,是很好的事情。但明示或暗示可以跟DLSS比,真的是XX比圈圈。
--
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