Proceedings from my presentation during EXIT FEST on the 24th of June 2026, in celebration of Geert Lovink and the Institute of Network Cultures’ departure from the Amsterdam University of Applied Sciences (HvA) on September 1, 2026.
The Digital Image is Non-Static
While we usually think of images as static objects, they are in fact never completely stable. Processing, use, and semiotics may all affect the life of the image: a photograph may exist as a momentary render, while also becoming evidence, or a symbol, depending on how, where, and by whom it is used or seen.
In contemporary digital imaging environments, this instability becomes more significant because the image is continuously (re-)processed. Within these environments, the image is both a surface activated through semiotic interpretation and an asset subject to technical, institutional, and operational procedures such as compression, classification, or moderation, just to name a few. Since these procedures are distributed across standards, platforms, and institutions, infrastructure is not external to the image. Instead, it forms part of the conditions via which the image processed, made available, and put to use. After these transformations, the visible surface of the image may remain the same (or appear similar), while its conditions may have changed. By “conditions of the image,” I thus mean the technical, institutional, and operational relations through which its accessibility, editability, and legibility are configured.
About the Proliferation of Image Types
The different ways in which images are (re-)processed, circulated, and put to use have contributed to a proliferation of image types.Technical images (as theorized by Vilém Flusser), poor images (Hito Steyerl), operational images (Harun Farocki), forensic images (Eyal Weizman and Forensic Architecture), post-photographicimages (William J. Mitchell), invisible images (Trevor Paglen), nonhuman photography (Joanna Zylinska), softimages (Ingrid Hoelzl and Rémi Marie), and poor chroma images (Michael Dieter) are just a few examples of this sprawling typology.
image composite of many image types
Each of these image types focuses on a particular condition (or configuration of conditions) of the image. Although historically and theoretically useful, they neither describe equivalent categories nor approach the image through the same theoretical framework. Different image types are therefore not aligned along a single axis. While the technical image centers its apparatus-based production, the post-photographic image describes a broader historical and technological transformation of photography. The poor image is defined primarily through its relation between circulation, degradation, accessibility, and value, while a poor chroma describes the sacrificial role of green within the temporal and composite conditions of tactical live video. So rather than forming a stable taxonomy, these types articulate different, yet sometimes overlapping, conditions.
Moreover, the same image may be described via different image types: a machine-readable CCTV stream may be used for facial recognition without being shown to a human viewer. The same stream may later be introduced as evidence in a court of law. Operational, invisible, and forensic images thus describe different conditions of the same image, some of which may coexist while others emerge from a specific context. When an image that functioned operationally is later treated as forensic evidence, it does not necessarily imply a visible change in the surface of the image. It instead reflects a shift in the conditions through which the image becomes legible. This shift also changes the criteria according to which the image is judged a ‘adequate’.
Fidelity as Accountability to a Particular Mode of Use
In signal processing, fidelity usually describes the degree to which an output reproduces an input. In imaging, however, this comparison becomes more complicated. Image fidelity may describe the relationship between a processed image and a source image or signal, but it may also concern perceptual quality, or the ability to discern provenance, required for an image to function, for instance, as evidence or assign ownership.
I therefore use fidelity more broadly to describe the relationship between how an image is expected to function and what it must preserve in order to do so. As such, fidelity is closely related to affordance and compromise. While affordance refers to the actions or uses that a system enables or makes easier, compromise describes how competing qualities and demands are negotiated within the technical and operational conditions of a processing pipeline. Fidelity describes the criteria
according to which these compromises are evaluated. The criteria that make these compromises acceptable may be specified or enforced by users, platforms, institutions, and technical standards and determine what counts as adequate detail, tolerable distortion or sufficient evidentiary continuity. Thus, fidelity is always accountable to a specific definition of adequacy.
For instance, lossy JPEG compression may reduce visual detail to enable faster transmission, while preserving enough perceptual information for the image to remain recognizable. In a forensic context, by contrast, the source image is usually be retained in its original form, even when access to it depends on obsolete technology. Any processing is performed on a copy, since forensic adequacy depends on maintaining an accountable relation to the source file and its provenance. Different imaging contexts thus answer to different definitions of fidelity. A resolution negotiates the compromises by which these different definitions of fidelity are met.
From Image Types to Resolutions
While resolution is often reduced to a number or quantitative metric, it should not be conflated with a fixed technical specification or density value. Following Jonathan Sterne, ‘definition’ could be a more precise term for the measurement of density of information. Resolution instead describes a broader process through which an image becomes a rendered instance.
During the process of resolving an image, compromises are negotiates following particular constraints, thresholds and modes of fidelity. The resulting configuration enables certain actions and forms of legibility, while other possibilities may be reduced, excluded, or deferred. Changes in technical, institutional, or operational conditions will re-resolve an image render. These changes may also affect the image’s epistemic status; for instance, compression artefacts, glitches, and synthetic aberrations, may be read as traces of the thresholds, incompatibilities, or failures involved in a particular process of resolution.
A process of resolution may be organized toward a particular use and may therefore make certain image-types more common. When a similar configuration recurs across images, it may be recognized as a broader technical, institutional, or historical pattern. This may lead to the particular image condition to be theorized, and eventually the coining of a new image type.
However, an image type does not correspond directly to a specific process of resolution. Instead, each image type centers certain relations within the configuration of a resolution, while leaving others less visible. The same rendered image may therefore receive a different image-type designation without being re-resolved: when an operational CCTV stream is introduced as evidence, its forensic status follows from a change in institutional use rather than from a visible or technical alteration. Image type thus describes the relation between an image andthe conditions under which it is understood as put to use as a particular kind of image.
Topologies of Compromise
Resolution Studies follows the image through the different situations in which it is processed, circulated, displayed, interpreted, and used. At each stage, different compromises may be made and different modes of fidelity may come into play. These decisions shape the image render that becomes available, while other possible configurations are reduced, deferred, or excluded.
Resolution Studies can thus develop a topology of compromise around a particular image render. These topologies describe the sites and stages at which compromises or trade-offs alter what a momentary image render can disclose, preserve, make available, or enable.
In this sense, Resolution Studies offers image theory a way to read the proliferation of newly coined image types through the resolution problems they articulate. Technical, poor, operational, forensic, synthetic, and other image types do not occupy equivalent positions within a single framework.  Instead, each of them centres on different sites or configurations of compromise. A topology of compromise makes these image types comparable without requiring them to be arranged within a fixed taxonomy.