Imatest provides customers with software, charts and equipment to meet and exceed image quality testing standards.

Imatest gives companies the right tools to test their image capture technology and has been a leader in image quality testing for over 10 years. Whether it’s still shots or video, visible light or infrared, Imatest has helped businesses in a variety of industries, including mobile, automotivemedical and manufacturing.

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Test for a variety of image quality factors at once using over 30 popular test charts. Test everything from sharpness, distortion, color, illumination and more.
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Ensure manufacturing outcomes meet product design requirements. Automate analysis modules to efficiently analyze image quality in testing environments.
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Automatic image acquisition provides real-time analysis of image quality parameters to speed up the testing process. Remove the need to process individual images.
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Most recent imaging science articles

Image Quality Testing for Webcams

Webcams are an increasingly vital tool for working remotely and staying connected with friends and loved ones. As such, webcam sales have experienced significant growth. We all know good and bad quality images when we see them, but quantifying a camera’s performance is critical for making design choices, sourcing components, and performing quality control. Developing these devices presents challenges common to the development of consumer cameras. Luckily, Imatest solutions can help overcome these challenges by providing reliable, robust, and repeatable analysis of key image quality factors. Imatest software, test charts, and equipment can even help certify your device according to popular video conferencing platform certifications. Webcam testing is made even more efficient and convenient thanks to the Imatest Device Manager, which allows for image acquisition directly from the device.

Sharpness and noise performance are critical for perceiving detail in an image. In fact, they are often the factors most associated with good image quality. Compression of the video file can also have a distinct effect on image quality, although it is often unavoidable when transmitting a live video stream across the internet. It’s important to understand how the webcam reproduces colors and tones so the color correction matrix and OECF curves can be tuned. Of course, more accurate color and tone reproduction do not always mean a more pleasing image. Distortion affects all systems, and it can be corrected with software once it is characterized. More information about testing these factors (and more) with Imatest solutions can be found below. 


One of the most important factors for creating a good image, sharpness is the ability of the camera system to resolve detail. This image quality factor is influenced by the lens optics, camera sensor, and image signal processing. Imatest provides multiple charts for sharpness testing, including ISO 12233:2017 compliant charts, all of which are fully supported by our software. More information about sharpness testing with Imatest can be found on our sharpness documentation page


Since the data capture by a webcam is meant to be transmitted across the internet, some form of compression is usually applied to the video stream to make the transmission faster and more reliable. However, this is frequently done at the expense of image quality, so it’s important to optimize the compression to maximize image quality and minimize file size. Imatest software also supports companded image files. The effects of various compression schemes can be compared using structural similarity index (SSIM). More information about SSIM testing with Imatest can be found on our SSIM documentation page


The way a camera system records color is key to its ability to make a pleasing image. Keep in mind that accurate color reproduction in the final image is not always visually pleasing (in fact, we tend to prefer stronger, more saturated colors over accurate representations); however, it’s important to characterize baseline system performance before applying color correction matrices to make color more appealing. Imatest provides industry-standard color measurement test charts, and Imatest Master software offers a range of color metrics. More information about color testing with Imatest can be found on our Colorcheck documentation page

Tone mapping

Tone mapping controls how various tones are represented and balanced in the final image. It is related to a system’s dynamic range performance, but the two are not interchangeable. Dynamic range is the full range of tones that can be captured, whereas tone mapping dictates how those tones are represented. This affects the image’s contrast and level of visible detail in bright or dark areas, and overall perceived brightness or darkness. Different tone mapping strategies can be applied for various lighting conditions. As with color measurements, it’s important to remember that accurate representation of the tones in a scene does not necessarily result in a pleasing image. We tend to prefer images with more contrast, as well as maximized detail in the highlights. Before subjective tone mapping can be achieved, it’s important to characterize the camera system’s baseline tonal response before adjusting for a better looking image. Tonal response can be measured with a range of gray-scale step charts along with Imatest software. More information about tonal response testing with Imatest can be found on our Color/Tone documentation page


Flare light can have serious effects on a camera’s dynamic range and tonal response. It is the result of stray light from reflections between lens elements and inside the lens barrel, and it can be caused by bright light sources in or near the field of view. Flare is easily visible when someone is using a webcam while sitting in front of a bright window. While uncontrollable lighting conditions can make flare difficult to avoid, special lens element coatings and lens design can help to minimize its effects. Flare testing can be achieved with Imatest software using the ISO standard 18844 test target. More information about flare testing with Imatest can be found on our Fare solutions page


Nearly all camera optics result in distortion to some degree, even if it’s not entirely noticeable. This is especially true of wide field-of-view lenses (which are often included on webcams) due to the geometry of the optical paths. However, software can correct for distortion so the final image appears more natural. First, the type and degree of distortion must be characterized for the given camera system. This is possible with test charts with regular patterns, such as checkerboards or dot patterns, along with Imatest software. More information about distortion measurement with Imatest can be found on our Distortion solutions page


Image noise is visible as random variation in pixel levels due to the photon nature of light and the thermal energy of heat. It is often described as “graininess” (a hold-over from the appearance of film grain) and is usually more visible in darker regions of the image. While it can never be entirely avoided, image noise should be minimized and signal to noise ratio (SNR) maximized to yield the best possible image sharpness and dynamic range. Low-light conditions, such as those commonly encountered by webcams used in dim indoor lighting, are particularly difficult to handle. Noise metrics can be calculated from grayscale patterns found on multiple Imatest test charts. More information about noise testing with Imatest can be found on our Noise solutions page

Timing / Frame Rate / Latency

Temporal metrics are important to video quality, especially when the goal is to transmit video across the internet for users to interact in real-time. Metrics such as timing, frame rate, and latency can be tested with specialized hardware such as the Camera Timing Test System

As more people work remotely now than ever before, quality webcams have experienced a surge in popularity. There is no shortage of challenges when developing high-quality, affordable webcams. To learn more about how Imatest test charts, equipment, and software can help you overcome these challenges, please feel free to contact us at

Correcting Misleading Image Quality Measurements

We discuss several common image quality measurements that are often misinterpreted, so that bad images are falsely interpreted as good, and we describe how to obtain valid measurements.

Sharpness, which is measured by MTF (Modulation Transfer Function) curves, is frequently summarized by MTF50 (the spatial frequency where MTF falls to half its low frequency value).


Describing and Sampling the LED Flicker Signal

High-frequency flickering light sources such as pulse-width modulated LEDs can cause image sensors to record incorrect levels. We describe a model with a loose set of assumptions (encompassing multi-exposure HDR schemes) which can be used to define the Flicker Signal, a continuous function of time based on the phase relationship between the light source and exposure window. (more…)

Validation Methods for Geometric Camera Calibration

Camera-based advanced driver-assistance systems (ADAS) require the mapping from image coordinates into world coordinates to be known. The process of computing that mapping is geometric calibration. This paper provides a series of tests that may be used to assess the goodness of the geometric calibration


Measuring camera Shannon information capacity with a Siemens star image

Shannon information capacity, which can be expressed as bits per pixel or megabits per image, is an excellent figure of merit for predicting camera performance for a variety of machine vision applications, including medical and automotive imaging systems.


Verification of Long-Range MTF Testing Through Intermediary Optics

Measuring the MTF of an imaging system at its operational working distance is useful for understanding the system’s use case performance. (more…)

Imatest Releases Version 2020.1

Imatest, a global image quality testing solution provider, is pleased to announce Imatest 2020.1 that adds new features on top of the major enhancements made in version 5.2. This new release further enhances the software with stability updates and regular improvements. See the Imatest Change Log for details.


Imatest EI Presentations Now Online

The research papers presented at this year’s Electronic Imaging Symposium (EI 2020) by Imatest engineers are now available. (more…)