Since its founding, Cloudinary's mission has been to help companies unleash the full potential of their media to create the most engaging visual experiences. In keeping with that quest, we support new codecs for images and videos as soon as possible.
Image formats, which are standards for digital images, can be uncompressed, compressed, raster based, or vector based. You determine the DNA of your images with the formats you adopt, each of which offering different capabilities. For example, rasters generate images with pixels; vectors, with vectors or proportional formulas. PNGs can display logos without background; JPEGs always come with backgrounds. This article explains the main properties of the various image formats, including their basic concepts and pros and cons.
As computer users, we constantly upload files, transferring them from one system to another over a network. You can perform uploads on a terminal, such as through the SSH File Transfer Protocol (SFTP) or Secure Copy Protocol (SCP), File Transfer Protocol (FTP) clients, or web browsers. Generally, you upload files to move data to a server or a managed service like cloud storage, but you can also send files between distributed clients.
JPEG images are either progressive or nonprogressive, depending on their encoding order, not politics.
Encoding of and decoding of nonprogressive occurs in this simple order: from top to bottom and from left to right. Consequently, when a nonprogressive JPEG is loading on a slow connection, you see the image’s top part first, followed by the other parts as loading progresses.
Welcome to the latest edition of the Responsive Images Guide!
In part 1, I laid out the big idea: a responsive image is a variable image – which adjusts itself to fit variable contexts.
In part 2, we looked at the most common way that an image can do exactly that: scaling itself up and down to fit viewports of different sizes and screens with different densities.
As a developer, it seems inefficient to serve a 2000kb JPEG image when we could compress images to optimize the performance without degrading the visual quality.
We are not new to this kind of responsibility. But our productivity will end up being questioned if we do not deliver fast. In order to do so, the community has devised several patterns to help improve productivity. Let's review few of these patterns based on their categories:
In part one (One pixel is worth three thousand words) of this turned-to-be-two-part blog post, I discussed one-pixel images and how well different image formats “compress” these images. I was surprised how much there is to be said about the matter. This was supposed to be a short blog post, describing one-pixel images and how they compress, and instead it became a glorious monster (and also a two part blog post…).
A couple of months ago while taking a break from implementing cool new features like q_auto and g_auto, I was joking in our team chat about how well various image formats “compress” one-pixel images. In response, Orly — who runs the blog — asked me if I’d write a post about single-pixel images. I said: "Sure, why not. But it will be a very short blog post. After all, there’s not much you can say about a single pixel."
If you make a copy of a copy of a copy, the quality will deteriorate with every ‘generation’. This problem is called ‘generation loss’. It is not difficult to understand why this happens with actual copier machines. Scanning and printing are not perfect, being based on noisy sensors and physical paper and ink, and the resulting noise will tend to accumulate.