Bitmaps are literally a bitmap

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  Likewise, don't miss the applications that every marketing professional should know and use ! Share Valentina GiraldoRock author vector Authorll image formats explained and evaluated for you Images are the most disseminated content on social networks (72.4%) and those that generate the most engagement (40.8%), according to the Social Media Trends 2017 survey (Brazil). Zuk Chagas Feb 21, 17 | 8 min read That is to say, sooner or later, the need to create images as part of your digital marketing strategy ends up arising , whether during the customization of a template, whether for social networks or for the creation of an e-book. And it is at that moment that we come across several strange acronyms that don't make much sense at first glance. You know, the ones that come at the end of the file name and don't seem to make much difference.

BUT THEY HAVE IT! They are the different image formats. To tell Bahamas WhatsApp Number the truth, the acronyms are the extensions corresponding to the formats. And that is what I will talk about today. But first, you need to understand what a format is and what types of images are. Image Types To begin, let's understand that, as already stated in our exclusive article on graphic design , there are two types of images, digitally speaking: Bitmap and vector . Don't confuse formats with types! Those two types of images will be covered in this article on image formats. They have some differences and directly affect the way they are used.





Bitmap Also known as a “bitmap” (literal translation) or a raster image, it is one of the most common types of images. Bitmaps are literally a bitmap. That means that the image is made up of various tiny points (pixels). Each of the pixels is assigned a color and, through X and Y coordinates, these colored pixels are positioned in a mesh and, thus, form an image. The photos are bitmaps. Vectors They are images that are based on polygons made up of points. These points are interpreted by the computer taking into account their distances. This being so, the vectors are infinitely scalable. You can increase a vector as much as you want, as there is no loss of resolution in the process.