It is often said that the more resolution a monitor has, the better the image quality. Well, if you are very lay in this area and if they talk to you about resolutions, that sounds like an unknown language to you, so don’t worry. Since we are going to teach you the relationship between image quality and resolution of your monitor.
The market is full of monitors of all kinds which are promoted with different resolutions and the higher the resolution, the better the image quality they provide. Most of our readers know very well what a pixel is and its relation to image quality. However, we decided to simplify it so that those less experienced in the field can be clear on this basic concept.
The number of pixels and the quality of the image are related.
The images we see on our PC screens today are represented on screens made up of millions of dots that we call pixels. Each of them is composed of very small lights in which each of them represents a color of the RGB spectrum, in such a way that by combining them the colors are generated. Then we have luminance, which is the light intensity of each color and can come from the lights themselves or from a separate panel.
On the PC side, we call each image that is seen on the screen an image or a frame and in terms of memory, what is stored in an orderly fashion is the color and luminance value combined into one piece of information and in a manner ordered. That is to say from the first pixel located at the top left to the last pixel at the bottom right. This information is transmitted dozens of times per second to the monitor or TV, all using a video interface such as DisplayPort or HDMI and using the graphics card’s display driver for it.
Thus, the pixel is the minimum information value of an image, there can be no image that has a resolution lower than one pixel and having fewer pixels also implies having less information. in the picture. So, logically, if we have an image with less resolution, the image quality will suffer.
What happens if we reduce the size of an image?
Many times, due to lack of space, we have been forced to reduce the resolution of an image, the result has often been that under our perception, the image does not seem to exist a loss of image quality. However, this is an optical illusion. Since depending on the distance from the monitor and the density of these on the screen, we cannot tell the difference if there is a greater number of pixels.
Technically, our vision is to perform “pixel” simplification, to achieve the process of simplifying an image so that it can be represented with fewer pixels. Obviously, the process does not always work and if the screen resolution is too small, details are lost. The process? Well, thanks to a mathematical formula, the values of the points in each area of the screen are taken into account and a new pixel is generated which contains the closest information.
Obviously with this we obtain that the image occupies less megabytes in storage, the problem we had is a process of destroying information that will not be recovered and therefore, in principle, it will be impossible to generate the same image at the original resolution. At best, we can expect an AI to hallucinate a higher resolution version of the image, but depending on whether we have enough information to do so or lack of it, it can create aberrations or images inaccurate.
The importance of file formats
There is another way to crop an image’s information and use image file formats, which may result in loss of detail or preserve the quality of the original image. In each of them, the key is that instead of storing the color information for each pixel as it is, the information is encrypted to be able to represent it with fewer bits and thus make it occupy less space. The downside is that a conversion process is required, performed by an algorithm responsible for reconstructing the original image.
However, this is not always the case and there are image formats such as JPEG which end up producing artifacts or errors if the information ends up being encrypted in a few bits. In other words, if it ends up compressing too much. This is where image AIs also come into play, but in a different way than increasing resolution. They learn to identify these common failures and how they occur and restore the image to its original quality, allowing them to be enjoyed taking up less space, but without losing quality.