Dots per Inch (DPI)

Resolution describes how many image points a digital file contains and how densely those points sit on a given area. In raster images, the motif is made up of individual pixels, each storing its own color value. The more pixels available for the same area, the finer the details, edges and color gradients appear.

DPI stands for dots per inch and indicates how many image points are output across a distance of 2.54 centimeters. DPI is therefore not a property of the image itself but a relationship between pixel count and physical output size. An image 3000 pixels wide prints ten inches wide at 300 dpi, or twenty inches at 150 dpi with visibly less sharpness.

Three terms are frequently mixed up in everyday use. Pixel dimensions such as 4000 × 3000 pixels are the absolute value and the actual substance of an image. PPI (pixels per inch) describes the pixel density of a screen, while DPI originally comes from printing technology and refers to the raster dots of an output device. In practice, DPI is now used for both.

The consequence matters: the dpi value stored in a file is nothing more than an entry in the metadata. If you change that value from 72 to 300 in an image editor without resampling the file, the image gains no additional information whatsoever. Only the intended output size changes.

For professional printing, 300 dpi at the final reproduction size serves as the benchmark. Catalogs, packaging and advertisements are calculated on this basis, which is why print originals are usually created as lossless graphic formats with a high pixel count. For large formats such as trade fair walls or posters, the value is considerably lower because the viewing distance is greater.

On the web, dpi is practically irrelevant. What counts here is the pixel dimensions in relation to the display area and to the pixel density of the end device. High-resolution displays expect images with double or triple the pixel count to stay sharp. At the same time, every additional pixel increases file size and therefore loading time. For online shops and websites this means a trade-off between sharpness and performance, best resolved through several derivatives of the same motif, from the detail view down to the thumbnail.

Image information that was never captured cannot be recovered afterwards. When an image is upscaled, new pixels are estimated from neighboring values through interpolation. The result looks soft, loses detail and shows artifacts at strong magnification. AI-supported methods achieve better results but likewise only add plausible content, not genuine capture data.

Vector graphics behave differently. Formats such as SVG describe shapes mathematically rather than through image points and can therefore be scaled freely. For logos and functional graphics this is the more reliable route, but for photography the option does not exist. Hence the basic principle: always archive originals at the highest available resolution and derive everything else from them.

This is exactly where Digital Asset Management comes in. In TESSA DAM, the high-resolution original is stored centrally as the leading version. All channel-specific variants are generated from it automatically through rendering, whether that is the 300 dpi print file, the compressed shop image or the preview for a sales document. Resolution, format and color space are not decided anew with every download but defined once as a rule.

For you as a user, this means no more incorrectly scaled files in circulation, and agencies or retailers receive the appropriate variant without asking. The original remains untouched while every channel gets precisely the resolution it requires.