Why Image Quality Analysis?

Today, the digital image is an everyday tool, both as a means of artistic expression and as a working tool in many disciplines, as well as an important field of discussion, research and dissemination.

As in any process, whether industrial, scientific or even artistic, understanding the scope of our tools and devices is a fundamental part of success.

Quality control allows us to systematize processes through the study and analysis of the tools that are part of our workflows, giving us feedback on the performance of each element involved in the production of our images. Thus, quality control in digital imaging is a tool to understand the performance of equipment and devices, to understand how a manufacturer has planned a process and whether it is more or less relevant to our workflow.

ImageQA has been designed in the context of the digitization of cultural goods and works of art in general, so that we can ensure the different quality thresholds required in the various recommendations and regulations. As well as, in general terms for the context of image applied to science, in order to define systematic capture methodologies.

Likewise, ImageQA is an excellent tool for teaching image and digital photography, since it allows us to establish a good number of exercises that facilitate the student's understanding of fundamental concepts of digital imaging. Similarly, ImageQA allows us to make comparisons between equipment and software in an objective way, avoiding biased discourses based on opinions about the qualities and benefits of no and other equipment.

ImageQA allows us to analyze the following quality indicators:

Color accuracy (delta-e), to evaluate the relevance of our color management workflows, particularly in scanning and product photography tasks where high fidelity in color reproduction is demanded.

Tone transfer, reported by the OECF (Opto Electronic Conversion Function) which allows us to evaluate the accuracy of how the different tonal ranges of a scene are transferred to our image, in order to highlight defects in exposure, in the balance between channels due to colour temperature problems, as well as to study the tone curves introduced by manufacturers during raw processing, etc.

The noise expressed through the Signal to Noise Ratio (SNR) allows us to understand the best response in terms of signal from a sensor for different gain levels, as well as the incidence of filters for noise reduction, dynamic range, etc.

Light falloff across a uniform surface is an analysis that helps us both to evaluate the uniformity of the illumination in a plane, for example, when digitizing certain elements in a reproduction table, but also helps us to understand the incidence of vignetting or light fall towards the edges of the lens, at different apertures of the diaphragm, different focal lengths, etc.

Sensitometry, which starts from a collection of images taken at different exposure parameters, allows us to establish the exposure accuracy of our measurement tools in relation to a given processing, in order to deduce correction factors or tone curves. The sensitometry tools are also interesting to study the stability of a flash flash, or its power ramps, in order to know the precision and stability of it.

The sharpness, described by the acuity through the metric of the MTF (Modulation Transfer Function) that together with other graphics like the ESF or LSF gives us information about the capacity to solve detail of a system.

And finally, with the possibility of performing most of the analysis in batches, that is, extracting the different metrics for a set of images in order to deduce the best performance from a set of settings or equipment tested.

Thus, imageQA allows us, along with the use of simple color charts, such as a Colorchecker or a Slanted Edge chart for the study of acuity, allows us to extract a good number of quality indicators from our cameras, software and ultimately workflows. Providing an added value of professionalism and control of the work to our customers.