Sometimes a technical term gets used without any thought to its meaning, and before you know it becomes an industry standard. This is the case with the term “image resolution”, which has become the standard means of describing how much detail is portrayed in an image. The problem is that the term resolution can mean different things in photography. In one context it is used in describing the pixel density of devices (in DPI or PPI). For example a screen may have a resolution of 218 ppi (pixels-per-inch), and a smartphone might have a resolution of 460ppi. There is also sensor resolution, which is concerned with photosite density on a sensor based on sensor size. You can see how this can get confusing.
The term image resolution really just refers to the number of pixels in an image, i.e. pixel count. It is usually expressed in terms of two numbers for the number of pixel rows and columns in an image, often known as the linear resolution. For example the Ricoh GR III has an APS-C sensor with a sensor resolution of 6051×4007, or about 24.2 million photosites on the physical sensor. The effective number of pixels in an image derived from the sensor is 6000×4000, or a pixel count of 24 million pixels – this is considered the image resolution. Image resolution can be used in the context of describing a camera in broad context, e.g., the Sony A1 has 50 megapixels, or based on dimensions, “8640×5760”. It is often used in the context of comparing images, e.g. the Sony A1 with 50MP has a higher resolution than the Sony ZV-1 with 20MP. The image resolution of two images is shown in Figure 1 – a high resolution image has more detail than an image with lower resolution.
Technically when talking about the sensor we are talking about photosites, but image resolution is not about the sensor, it is about the image produced from the sensor. This is because it is challenging to attempt to compare cameras based on photosites, as they all have differing properties, e.g. photosite area. Once the data from the sensor has been transformed into an image, then the photosite data becomes pixels, which are dimensionless entities. Note that the two dimensions representing the image resolution will change depending on the aspect ratio of the sensor. So while a 24MP image on a 3:2 sensor (APS-C) will have dimensions of 6000 and 4000, a full-frame sensor with the same pixel count will have dimensions of roughly 5657×4243.
Increasing image resolution does not always mean increasing the linear resolution, or detail in the same amount. For example a 16MP image from 3:2 ratio sensor would produce an image with resolution of 4899×3266. A 24MP images from the same type of sensor would increase the pixel count by 50%, however the vertical and horizontal dimensions would only increase by 20% – so a much lower change in linear resolution. To double the linear resolution would require an increase in resolution to a 64MP image.
Is image resolution the same as sharpness? Not really, this has more to do with an images spatial resolution (this is where the definition of the word resolution starts to betray itself). Sharpness concerns how clearly defined details within images appear, and is somewhat subjective. It’s possible to have a high resolution image that is not sharp, just like its possible to have a low resolution image that has a good amount of acuity. It really depends on the situation it is being viewed in, i.e. back to device pixel density.