And I'm really sorry if you're one of the lucky ones who's never noticed this, because now I point it out,

如果你在此之前都很幸運地沒有發現，那我得先跟你說聲抱歉，因為在我點出來之後，

now I artificially increase the brightness on the dark parts in this video so you can see what the shadows behind me actually look like....

在我刻意地調高本影片黑暗部分的亮度之後，你就能看到我身後的陰影其實看起來...

Now, you'll notice.

現在你就能察覺到了。

In movie trailers, in dark scenes in even prestige television, in YouTube videos where there are nice, calm gradient backgrounds: you see this dreadful color banding.

在電影預告片內、在就算是有著高預算電視節目的黑暗場景中、在有著沉穩灰階背景的 YouTube 影片裡，你都能看到這些醜陋的塊狀色帶。

There are three reasons for it.

這種現象的出現有三個原因。

And the first is that there aren't enough colors.

第一個是，我們能呈現出的色彩不夠多。

Alright, I'll, I'll turn the lights on.

好啦，讓我先把燈打開。

In most modern digital video, there is a grand total of about 16.7 million possible colors.

在大多數的現代數位影片中，總共能呈現出大約 1 億 6700 萬種可能的顏色。

And that number comes from how your screen works.

這個數量取決於螢幕的運作方式。

When you watch a video, your phone, computer or TV takes that compressed digital signal that's being sent to you, and it converts it into instructions.

當你在觀看一部影片時，你的手機、電腦或是電視會接收傳輸給你且被壓縮過的數位信號，並將它們轉化為指令。

Those instructions go to the screen, which changes the brightness of each of the millions of red, green, and blue lights that make up your screen, up to 60 times a second, perfectly.

這些指令會傳輸給螢幕，而螢幕會以最多每秒 60 次的速度，完美地更動內含的數百萬個紅色、綠色與藍色的燈泡亮度。

It's incredible technology that we just take for granted.

我們現在把這樣的科技當作理所當然。

But those little lights can't be adjusted to any brightness.

但這些小小的燈泡可沒辦法調整的任何的亮度。

The simplest digital signal would just tell the screen whether to turn each light on or off.

最單純的數位信號只會告訴螢幕該打開或關閉哪個燈泡。

Each instruction would take a single bit, a single one or zero.

每一次的指令都會花費一個位元，也就是一個 1 或 0 的信號。

So for each pixel, each combination of red green and blue, that gives you eight possible colors: two times two times two.

所以對於每個像素來說，藉由組合紅綠藍三種顏色，便能給你八種不同的顏色：二乘二乘二。

Which doesn't look great.

看起來實在不怎麼樣。

So, okay, let's add another bit for each color.

所以現在讓我們再為各個顏色多加點變化吧。

Two bits gives us four options for each light: off, dark, sorta-bright, and completely on.

多兩個位元能讓我們為每個燈泡提供四個選項：關閉、灰暗、有點亮和完全開啟。

Now we've got four times four times four, 64 colors!

現在我們就有四乘四乘四，總共 64 種顏色了！

Still doesn't look great.

看起來還是不怎麼樣。

For a modern screen, you need eight bits for each pixel, so you've got 256 shades each of red, green, and blue, which gives you those 16 million colors that you're used to.

在一個現代的螢幕中，每個像素需要八位元，所以紅、綠與藍色都各有 256 種色階，總共能提供你所習慣的 1600 萬種色彩。

And that ought to be enough, right? It seemed to be, when the standards were written.

這樣應該夠了，對吧？至少在制定標準的當時，看起來是足夠了。

And to be fair, every bit you add means more data to transmit and more expensive equipment.

平心而論，每增加一個位元就代表需要傳輸更多的資料，還需要更加昂貴的設備來配合。

It seemed like a pretty good compromise at the time.

在當時，這看起來是個挺不錯的妥協點。

Professionals, like people working in digital cinema, they go further, they might use ten bits for each pixel, giving them about a billion total possible colors instead.

而對職業工作者，例如在數位電影院工作的人們來說，他們則會更進一步，每個像素可能會用上十位元，藉此獲得將近十億種可能的顏色。

And you may well have a fancy screen that can show those more precise billion colors, but the picture quality is determined by the weakest link in the chain.

而你可能還真的擁有一台能夠精準顯示這十億種顏色高階螢幕，但其實影片品質的優劣是由整個串流過程中最薄弱的環節所決定的。

A ludicrously expensive HDR monitor isn't going to fix the color banding on that regular YouTube video.

一台有著天價的 HDR (高動態範圍成像) 螢幕並無法解決一般 YouTube 影片上的塊狀色帶問題。

Anyway, it was decided that 256 shades each of red, green, and blue, combined however you like, that should be enough for most people.

無論如何，能夠以 256 種不同程度的紅、綠、藍光任意組合對大部分人來說應該已經足夠了。

And for almost everything, it is.

而在大部分狀況下，這樣確實就夠了。

But at full resolution, this video is 1,920 pixels wide.

但以本影片來說，在完整解析度下的寬度將會是 1920 像素。

And there are only 256 shades of green.

而可以用上的綠色則只有 256 種。

So if I have a green gradient across the whole video, even if you use every single shade of pure green that's possible on this format, then you're still going to have a color band every seven or eight pixels.

所以要是我讓綠色的漸層橫跨一整個影片，就算用上了這個格式下所有可用的純綠色，你仍然會在每七到八個像素之間看到一個個綠色的塊狀色帶。

And if everything's much darker than that, suddenly you might only have half a dozen different shades of green available across the whole picture.

而要是整個畫面再變得更暗一些的話，突然間你可能在一整張圖片上只會有六個不同的綠色色塊。

Even if you're using a bit of red and blue in there as well, there just aren't that many available dark colors.

就算用上了一點點的紅色和藍色也一樣。我們就是沒有那麼多可以用上的暗色色彩。

But if you've got plain, bright background, why doesn't that have color-banding all over it?

但當移動到一個純色的亮色背景時，為什麼上面不會全都是塊狀色帶？

Well, the second reason is how human eyesight works.

這就要說到第二個原因了，那就是我們人類看東西的方式。

There is color banding all over this video. Right now.

其實塊狀色帶現在正遍布這個影片。

If we take a sample of the bright gradient behind me and massively increase the contrast, you can see it's there... but normally, it's invisible.

把我深厚的一塊亮色背景拿出來，然後把對比度急遽拉高，你就能看到這些色帶了。但是通常狀況下，你看不到它們。

And that's because while the absolute difference between two bands is still the same, the relative difference is tiny.

這是因為儘管兩個色帶之間的絕對差異是相同的，它們的相對差異卻小得多。

It's the same reason that this chart looks a lot closer than this chart.

這和右邊這張圖表的兩個數值，看起來比左邊這張圖表的兩格數值還要更接近的原因。

Going from 201 to 202 feels like a tiny change, but going from 1 to 2 is a doubling.

從 201 到 202 感覺是個很微小的變化，但從 1 到 2 則是把數值翻了一倍。

Even in both cases, the absolute change is the same: one, we perceive one as being bigger than the other.

然而在兩個例子之中，改動的數值都一樣是 1，但我們仍會仍為其中兩者的差異更大。

But even if you don't have enough colors, you can break up gradients another way. You can use dithering.

就算你沒有足夠的顏色，仍能用另一個方法來突破色彩梯度的限制。你可以用上圖像抖動技術。

Instead of going from one color to another at a line, you can steadily transition from one to the other.

與其直接從一個顏色切換到另外一個顏色，你可以穩定地慢慢轉換。

You can make the boundary fuzzy, so that from a distance the colors appear to blend.

你能模糊不同顏色間的界線，讓你隔著一段距離看的時候，使顏色看起來融合在一起。

And if you're filming a real-life scene, then that'll happen in-camera, the natural light and the noise in the signal and the sensor will do that for you.

若你拍攝的是現實場景，那這一切處理都會在鏡頭下完成。自然光線、雜訊與感測器會幫你完成所有工作。

And it actually works really well, it more or less solves the problem... but it won't look like that here.

而這其實運作得挺好的，多多少少解決了問題... 但沒辦法解決在 YouTube 這裡的問題。

And that brings me to the third reason: compression.

這就帶到了我們第三個原因：影片壓縮。

A raw HD video, uncompressed, needs somewhere around a gigabit per second of data.

一個未處理的 HD 高解析度影片在沒有壓縮的情況下，每秒的資料需要占據約 1 Gb。

Even if you have an internet connection that can somehow support streaming all that, it's incredibly wasteful and expensive to use all that data.

就算你有著能夠支撐串流這樣資料量的網路連線環境，這樣利用資料不但相當浪費，也非常昂貴。

So every streaming service, YouTube, Netflix, everyone, uses lossy compression:

所以包含 YouTube 與 Netflix 等的所有串流服務，每一家用的都是破壞性資料壓縮法：

a program called an 'encoder' takes a massive high-quality video file, and then throws away fine detail to save data.

一個稱作「解碼器」的程式會解析一個巨大的高品質影像檔案，然後捨去掉精密的細節來節省資料量。

The more the video is compressed, the worse it looks, but it'll work on slower and slower connections, and it'll be cheaper and cheaper to run your streaming service.

影片被壓縮得越多，看起來就越糟糕，但是也越能在更慢的網路連線下播放，並對於串流服務商來說也更加便宜。

But at some point, the viewers are going to notice that the picture doesn't look great.

然而到了一定程度之後，觀眾將會發現影像品質看起來不是很理想。

But the encoder, the compression software, is written by very clever people:

但是寫出作為解碼器壓縮軟體的人們非常聰明，

and it works out which bits of the scene the viewer is probably going to be interested in, and puts most of its effort into making that part look good.

解碼器會判斷出場景中的哪些部分是觀眾可能會有興趣的地方，並盡其所能把該部分漂亮地顯現出來。

And that's usually a bright, sharp part of the scene, something well lit and in focus, and probably the bits that are moving.

這些地方通常是場景中明亮、鮮豔的部分，有好好打上光線且聚焦正確，還有可能是正在移動的部分。

Now there are exceptions, where there's some slow, menacing threat out of focus in the background,

但仍然會有例外情況，例如背景中可能有個刻意失焦，緩慢移動著的可怕威脅之類的，

but for almost every scene, if it's dark, or out of focus, chances are the director and the viewer doesn't care about it.

但幾乎所有的場景中，只要是漆黑一片或是失焦的部分，絕大多數的情況下代表導演和觀眾不會在乎那部分。

So the encoder doesn't care about it either: if there are only fifty kilobits, fifty thousand ones and zeros available to describe each frame of video,

因此解碼器也不在乎：如果每個影片的每一禎只能用上 50 Kb ，也就是只有 5000 個 0 和 1 可以用的話，

then the encoder will make sure that most of those are spent on where the viewer's likely to be looking.

解碼器會確保這些資源被花在觀眾最有可能關注的地方。

All that dithering, all the fancy stuff in the background?

那些在背景中的抖動和精細的畫面？

Too expensive. Smear it out into just big blocks of solid color, no-one'll notice.

太貴了。直接把它們變成一塊塊色塊就好，反正沒人會察覺。

And we won't.

而我們確實不會。

Unless it's also very dark. At which point, there will be something nasty lurking in the shadows.

除非場景真的非常暗，於是陰影中就出現了躲藏在其中的惡毒色塊。