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  • If you put a colorful image into photoshop or instagram and blur it, youll see a weird,

    如果你把一張彩色圖片放進Photoshop 或instagram開模糊,你會看到相鄰亮色間

  • dark boundary between adjacent bright colors.

    有一圈奇怪的暗色邊緣。噁!在真實世界,

  • Yuk!

    失焦的顏色會平順地從紅→黃→綠混合─ 不是紅→棕→綠!

  • In the real world, out of focus colors blend smoothly, going from red to yellow to green

    這種混色問題也不限於相片模糊功能─幾乎任何時候

  • not red to brown to green!

    電腦模糊照片或軟體使用透明邊緣時,

  • This color blending problem isn’t limited to digital photo blurring, either – pretty

    就會看到這類恐怖的渣渣。

  • much any time a computer blurs an image or tries to use transparent edges, youll see

    這醜東西有個很簡單的解釋,和很簡單的解法。

  • the same hideous sludge.

    一切始於我們如何感受亮度。

  • There’s a very simple explanation for this ugliness – and a simple way to fix it.

    人類視覺一如聽覺,大致以對數級的相對尺度感測,

  • It all starts with how we perceive brightness.

    也就是它對一個燈泡變成兩個燈泡的亮度差, 感受遠比101個燈泡

  • Human vision, like our hearing, works on a relative, roughly logarithmic scale: this

    變成102個燈泡還強烈,儘管物理亮度的增長相同。

  • means that flipping from one light to two changes the percieved brightness a TON more

    我們的眼睛和大腦對背景全黑時的亮度小差異

  • than going from a hundred and one to a hundred and two, despite adding the same physical

    遠比對背景全亮時的同等差異敏銳。

  • amount of light.

    遠比對背景全亮時的同等差異敏銳。

  • Our eyes and brains are simply better at detecting small differences in the absolute brightness

    反觀電腦與數位感測器,完全基於擊中光感測器的

  • of dark scenes, and bad at detecting the same differences in bright scenes.

    光子數量顯示亮度,因此光線增加多少就感測到多少,

  • Computers and digital image sensors, on the other hand, detect brightness purely based

    無關背景亮度。

  • on the number of photons hitting a photodetectorso additional photons register the same

    儲存數位照片時, 電腦會記錄每個像素裡每種單色的亮度值─

  • increase in brightness regardless of the surrounding scene.

    紅、綠、藍,通常0就代表亮度為零

  • When a digital image is stored, the computer records a brightness value for each colors

    而1就代表100%亮度。 因此0.5看起來是1的一半亮,是否?

  • red, green and blueat each point of the image.

    非也。這個顏色看似半白半黑,但這是由於

  • Typically, zero represents zero brightness and one represents 100 percent brightness.

    我們的對數視覺,以物理上的絕對亮度而言,它僅有

  • So 0.5 is half as bright as 1, right?

    純白的五分之一多光子。 更瘋狂的是,亮度值0.25的圖像僅包含純白光子數的

  • NOPE.

    二十分之一!

  • This color might LOOK like it’s halfway between black and white, but that’s because

    數位圖像設計成比物理真實更暗有個好理由:

  • of our logarithmic visionin terms of absolute physical brightness, it’s only

    記住,人類視覺更容易察覺黑暗背景中的微小亮度變化

  • one fifth as many photons as white.

    數位圖像時代早期的軟體工程師, 會以此作為節省硬碟空間的招數之一。

  • Even more crazy, an image value of 0.25 has just one twentieth the photons of white!

    數位圖像時代早期的軟體工程師, 會以此作為節省硬碟空間的招數之一。

  • Digital imaging has a good reason for being designed in this darker-than-the-numbers-suggest

    這把戲很容易:當數位相機拍了張照,與其儲存

  • way: remember, human vision is better at detecting small differences in the brightness of dark

    原先的亮度,不如存其正平方根─導致暗色擁有較多

  • scenes, which software engineers took advantage of as a way of saving disk space in the early

    儲存點,亮色有較少儲存點,大致模仿了

  • days of digital imaging.

    人類視覺的感受方式。當你需要在螢幕播放影像,

  • The trick is simple: when a digital camera captures an image, instead of storing the

    只要平方回去就能還原色彩。

  • brightness values it gives, store their square rootsthis samples the gradations of dark

    一切安好─直到你打算修圖。例如模糊效果,

  • colors with more data points and bright colors with fewer data points, roughly imitating

    是將像素色彩混成周遭像素顏色的平均。太簡單啦。

  • the characteristics of human vision.

    但你在平方前和平方後做此步驟

  • When you need to display the image on a monitor, just square the brightness back to present

    會得到不同結果!很不幸,多數電腦軟體都會弄錯。

  • the colors properly.

    會得到不同結果!很不幸,多數電腦軟體都會弄錯。

  • This is all well and gooduntil you decide to modify the image file.

    例如你想模糊紅色和綠色的邊界,你會期待中間是

  • Blurring, for example, is achieved by replacing each pixel with an average of the colors of

    半紅半綠的顏色,而懶惰的多數電腦只會把圖像檔中的

  • nearby pixels.

    亮度相加除以二,忘了真正的亮度已經被相機平方根

  • Simple enough.

    以便儲存!因此平均值會太暗,正是因為

  • But depending on whether you take the average before or after the square-rooting gives different

    兩個正平方根的平均,必不大於兩數平均的正平方根。

  • results!!

    為了正確混合紅色和綠色並避免噁爛污漬,電腦理當

  • And unfortunately, the vast majority of computer software does this incorrectly.

    先平方兩者的亮度以還原被平方根的影像,再來平均,

  • Like, if you want to blur a red and green boundary, you’d expect the middle to be

    再平方根回去,你看這好棒棒啊,真正的黃色!

  • half red and half green.

    不幸的是,大多數軟體,從iOS到instagram到photoshop

  • And most computers attempt that by lazily averaging the brightness values of the image

    的預設,都用了懶惰又愚蠢的錯誤平均步驟。

  • FILE, forgetting that the actual brightness values were square-rooted by the camera for

    雖然photoshop和其他專業軟體有進階設定可以調整,

  • better data storage!

    讓你能用數學和物理正確的方式混合,

  • So the average ends up being too dark, precisely because an average of two square roots is

    然而美麗不該作為預設值嗎? (這就是精確數學的威力!)

  • always less than the square root of an average.

  • To correctly blend the red and green and avoid the ugly dark sludge, the computer SHOULD

  • have first squared each of the brightnesses to undo the camera’s square rooting, then

  • averaged them, and then squared-rooted it backlook how much nicer it is!!

  • Unfortunately, the vast majority of software, ranging from iOS to instagram to the standard

  • settings in Adobe Photoshop, takes the lazy, ugly, and wrong approach to image brightness.

  • And while there are advanced settings in photoshop and other professional graphics software that

  • let you use the mathematically and physically correct blending, shouldn’t beauty just

  • be

  • the default?

If you put a colorful image into photoshop or instagram and blur it, youll see a weird,

如果你把一張彩色圖片放進Photoshop 或instagram開模糊,你會看到相鄰亮色間

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B1 中級 中文 亮度 軟體 電腦 燈泡 模糊 平方

電腦顏色被破壞了 (Computer Color is Broken)

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    林宜悉 發佈於 2021 年 01 月 14 日
影片單字