Hi everyone! This week I will – finally – explain the concept of resolution. It’s a broad and confusing topic. Then, I will split this post in two parts. Let’s get started!


The basic concept of resolution of an image refers to the amount of detail that can be seen on it. This term is used to describe – in everyday language – the concept of sharpness or definition.

In technical terms, resolution is the amount of pixels that fit in a linear unit. In other words, it establishes the relation between:

  • A – The size of the image in pixels – that depends on the capture device.
  • B – And the physical dimensions reproduced by the output device – on screen or printed.

This means that we are talking about the density of pixels. Its measurement unit is: pixels per inch (PPI). So, if your image has a high number of PPI, it has higher resolution. Simple, right?

However, every device that we use for displaying content has a limited capacity. Some of these limitations are technical and depend on how they “translate” the pixels of an image. Pixels are differently “built” on each device: TV, smartphone, printed documents,…

Consequently, resolution depends on the output device. In this first part of the post, I will focus on screen resolution.


According to the manufacturer, the screen of my laptop has the following features:

  • Screen Resolution: 1.366 x 768 pixels. It can display up to 1.049.088 pixels. As you can read, it refers to the size in pixels, not to quality/definition. If you want to know the size of your screen, just click here.
  • Diagonal = 15,6”: This is the measurement – in inches – of the diagonal of the screen. 1 Inch=2,54 cm.
  • Aspect Ratio = 16:9: It refers to the screen proportions. You can read more about it here.

However, this information doesn’t tell – directly – how good is the resolution of my screen. Then, how many PPI has my screen?

In order to calculate the PPI, we need to know the vertical and horizontal size – in inches – of the screen. Then, we divide the pixels of each side by its size in inches. Voilà!

If you want to do it even more simple, check this website.

As you can see, the screen has real pixels with specific physic dimensions. In fact, they are not “pixels” but “light points” that reproduce them.

In computers, the OS will recommend us to set up the best resolution possible for our screen. In my case it is: 1.366 x 768 pixels. Then, if we visualize an image at 100% of its size:

  • Each pixel of the image will be reproduced by 1 pixel of the screen. Makes sense, right? The image will be displayed at its maximum quality, 100%size.
  • If we zoom in: 1 pixel of the image will be reproduced by more than 1 pixel of the screen. Then, the final image will have less quality.
  • If we zoom out: the image must compress/combine its pixels in order to fit them into the pixels of the screen. Then, the image will lose information. Remember that 1 pixel of the screen only can reproduce 1 pixel of the image.

These statements allow us to develop the following logical deductions:

  • The resolution of an image – PPI – is not important when you visualize it on screen. The size in pixels is what really matters.
  • An image at 100% will be bigger on screen if it contents a big amount of pixels.
  • The image quality/definition will be limited by the quality of the visual content and by the capacity of the screen that reproduces it.

What is more, each pixel of our screen is composed by 3 subpixels in RGB colors – Red/Green/Blue. These turn on/off depending on what color they need to represent.

As you know, the pixels of our screen are organized in rows and columns. However, subpixels can be placed in diverse positions depending on the technology of the manufacturer. This allows us to get even more optimized results, placing more pixels per inch or just improving the quality of each pixel in the same space.

Well, if you want to know more about this topic, you should check this post. Next week, I will continue with the second part of this post. I will talk about: resolution for printing, physic size and weight of an image. Thanks for reading! 🙂

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