图形学与人机交互2014alvyray.com编辑精选
像素不是小方块 (1995)
A Pixel Is Not A Little Square (1995)
进阶 · 约 20 分钟读完前置知识：信号采样基础、图像重建基础、计算机图形学基础
导读
这篇 1995 年的经典备忘录讨论数字图像中像素应如何理解：像素不是有面积的小方块，而是对连续图像的采样点，重建连续图像需要合适的重建滤波器。作者 Alvy Ray Smith 借此澄清计算机图形学中常见的“像素=小方块”误解。
HN 关注点：是因为它触及图形学/图像处理中“像素到底是采样点还是小方块”的经典争论，并延伸到现代显示技术、抗锯齿和 alpha compositing。
后来怎么样
这篇备忘录成为图形学中讨论像素、采样与图像重建的经典参考，澄清了“像素=小方块”的常见误解，并影响了抗锯齿与图像重建的教学和讨论。
HN 评论精选
这几条评论里：质疑 1 补充 3
补充主张像素重建、细线渲染等问题需靠现代用户研究而非理论争论来定，并质疑常见的小方块加忽略 gamma 做法是否真的更好。
我想这篇被翻出来，部分是因为最近关于 alpha compositing 的讨论。我们迫切需要基于用户研究、使用现代显示技术的研究来回答几个基本问题：* 哪种重建滤波器效果最好？对矢量（文字）和自然图像是否相同？这里的“最好”确实指对比度（锐度）和没有可见伪影。* 对很细的线条渲染（与文字相关），哪种 gamma 曲线能让不同子像素相位下的线宽看起来相等？它如何随显示器 dpi 变化？（提示：很可能不是线性亮度）* 哪种 gamma 曲线能让黑底白线和白底黑线的细线看起来宽度相等（也与文字相关）？（提示：很可能不是线性亮度）我见过很多讨论，人们觉得自己能从第一性原理回答这些问题，也有相应论点说按“正确”方式做出来的结果，不如把像素当成小方块（即重建时用 box filter）并忽略 gamma（从而在 alpha compositing 时实际上使用感知色彩空间）这种常见假设更讨喜。我认为这些问题不能靠辩论解决。用户研究可能不难做；在线问卷大概能得到“足够好”的结果，尽管达不到学术严谨标准。
raphlinus查看英文原文
I imagine this came up partly as a result of the recent alpha compositing discussion. We desperately need some research, based in user studies and using modern display technology, to settle some basic questions: * What reconstruction filter gives the best results? Is it the same for vector (text) and natural images? By "best" I do mean contrast (sharpness) and lack of visible artifacts. * For rendering of very thin lines (relevant to text), what gamma curve gives the perception of equal line thickness across the range of subpixel phase? How does it vary with display dpi? (Hint: it's likely not linear luminance) * What gamma curve yields the perception of equal width of black-on-white and white-on-black thin lines (also relevant for text)? (Hint: likely not linear luminance) I've seen a number of discussions where people feel they are able to answer these questions from first principles, and corresponding arguments that doing these in a "correct" way gives results that are less visually appealing than the common assumptions of treating a pixel as a little square (so doing a box filter for reconstruction) and ignoring gamma so effectively using a perceptual color space for the purposes of alpha compositing. I posit that these questions cannot be solved by argumentation. I think user studies might not be very difficult to do; you could probably get "good enough" results by doing online surveys, though this wouldn't pass standards of academic rigor.
质疑认为“像素=小方块”虽在理论上不精确，但对计算机实现和教学非常实用，类比向量不必拘泥于抽象定义。
像素就是 picture element，一幅图像的元素，名字就是这么来的……但把像素想成排列在矩形网格上的小方块非常有用，因为计算机就是这样处理它们的，而不是当成点采样。这篇文章让我想起很多数学文本坚持向量不是数字元组，不能把向量想成方向与大小以外的东西；技术上也许对，但计算时把向量当数字有用得多。进入更抽象的数学、向量包含多项式等代数对象时，你早已习惯，随便把它们想成飞行的墨西哥卷饼都行。教图形编程时，我还会继续告诉学生像素像小方块。
bjourne查看英文原文
A pixel is a picture element. An element of a picture. Hence the name... It turns out that thinking of them as little boxes arranged in rectangular grids is very useful. Because that is how computers deal with them. Not as point samples. The article reminds me of the many mathematical text I've read insisting on that vectors are not tuples of numbers. That thinking of them as anything other than directions with magnitudes is wrong. Technically, that might be correct but vectors-as-numbers is much more useful when calculating with them. When you get into more abstract mathematics, and your vectors contain other kinds of algebraic objects, such as polynomials, you are already so accustomed with them that you can think of them as flying burritos if you like. When I teach graphics programming, I will continue to tell students that pixels are like little boxes.
补充指出现代 LCD/LED 显示让像素更接近小方块，因此重建的最佳方式与 1995 年 CRT 时代不同，但论文理论仍成立。
这篇文章是经典，图形学人必读；但别忘了它写于 LCD 显示器之前。今天的像素实际上比 1995 年的 CRT 更接近小方块。这并不改变 Alvy Ray 论文中的理论或真理性，但确实意味着“完美重建”已经不同于当年。
dahart查看英文原文
This piece is a classic and a must-read for graphics people, but do remember that this was written before LCD displays. Today’s pixels actually are little squares to a much greater degree than CRTs in 1995. That doesn’t change the theory or truth in Alvy Ray’s paper, but it does mean that the perfect reconstruction isn’t the same now that it was then.
补充提出六边形像素网格和错开 RGB 子像素更合理，虽然对现有图形编程习惯不友好。
几年前我在 Quora 上写过这个，回答为什么像素是方的（并很快澄清我把它理解为“为什么它们排列在矩形网格上”）：https://www.quora.com/Why-are-computer-pixels-square/answer/Rob-Brown-13 从那以后我想得越多，越觉得我们应该用六边形像素表示图像（即排列在六边形网格上），并且彩色图像应把红、绿、蓝子像素的中心点当作并不完全重合。（帖子第三张图展示了它们会如何排列，实际上和某些显示器上的排列相似。）对在像素级别工作的图形程序员来说会稍难处理，至少需要重新学习一些东西。但它在很多方面更合理。六边形是更好的“圆填充”方式（你在桌上摆一堆硬币就会注意到），而且现实显示器往往本来就让红绿蓝子像素彼此错开。（有不是这样的吗？）显然现在很难改变这种事，但我仍觉得这个想法迷人，也吸引我这种 OCD 效率控。
robbrown451查看英文原文
I wrote this on Quora several years ago, answering the questions of why pixels are square (and quickly clarified that I interpreted it as "why are they laid out on a rectangular grid?"): https://www.quora.com/Why-are-computer-pixels-square/answer/Rob-Brown-13 The more I've thought about it since, the more I think we should represent images with hexagonal pixels (i.e., laid out on a hex grid), and that color images should treat the center points of red, green, and blue subpixels as not being right on top of each other. (the third image in the post shows how they would be arranged, which is actually similar to how they are on some displays) It would be a little harder to deal with for graphics programmers who are working at a pixel level, or at the least, it would require a bit of relearning. But it makes more sense in so many ways. Hex is just a better way of "circle packing" (as you notice if you arrange a bunch of pennies on a table), and of course real world displays tend to have the red, green and blue subpixels offset from one another anyway. (are there any that don't?) Obviously it isn't easy to change something like this at this point, but still, I find the idea fascinating, and appealing to the OCD efficiency fan in me.
相关资源
从这篇论文所有 HN 讨论帖的全部评论里整理出来的链接。
- 代码
- github.com/harfbuzz/harfbuzz被提到 2 次
- 视频与演讲
历次讨论
- 2014Hacker News 讨论帖118 分 · 64 评
- 2019Hacker News 讨论帖143 分 · 78 评
- 2021Hacker News 讨论帖81 分 · 70 评
- 2025Hacker News 讨论帖30 分 · 29 评
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