Image Quality Factors are also called Key Performance Indicators (KPIs).
Image Quality Factor Video Series
Image Quality Video Series: Sharpness
Image Quality Video Series: Noise
Jan 16, 2017
The highest quality images are created by optimizing many key image quality factors. Noise is an undesirable random spatial variation, visible as grain in film, or pixel level fluctuation in digital images. Learn how Noise effects your camera system using Imatest.
Image Quality Video Series: Chromatic Aberration
Feb 21, 2017
Lateral chromatic aberration (LCA), AKA lateral chromatic displacement (LCD) and “color fringing”, is a lens aberration that causes colors to focus at different distances from the image center. It is most visible near the corners of images. In this video, we will explain the techniques used to measure for LCA.
Image Quality Video Series: Dynamic Range
May 16, 2017
The highest quality images are produced by optimizing many key factors. Dynamic Range is characterized by the ratio between the highest light intensity that a camera system can capture and the darkest tones that become indistinguishable from noise. Dynamic range measurements are useful for optimizing system performance and for verifying camera design specifications. Informed consumers seek camera systems with superior dynamic range, which can capture information in dark shadows while maintaining detail in brighter areas.
Image Quality Video Series: ISO Sensitivity & Exposure Accuracy
Image Quality Video Series: Uniformity
Jun 9, 2017
Lens shading, Light falloff & Vignetting:
Where your image becomes darker the further you get from the center. This is due to the radial nature of the lens which collects more light in the center. It can be particularly strong with wide angle lenses. Non-uniformity is also caused by the chief ray angle of light incident to the sensor which has reduced quantum efficiency as the angle increases.
Summary table— Image quality factors and corresponding test charts and modules | ||||||
Sharpness | Noise | Dynamic range, tone, & contrast | Color accuracy | |||
Lens Distortion | Uniformity | Blemishes | ISO Sensitivity | |||
Lateral Chromatic Aberration | Lens Flare (Veiling Glare) | Color Moiré | Artifacts | |||
Data compression losses | Dmax | Color gamut | Texture Detail |
Overview of image quality and Imatest measurements
Image quality is one of those concepts that’s greater than the sum of its parts. But you can’t ignore the parts if your goal is to produce images of the highest quality. Every image quality factor counts.
This page introduces the key image quality factors and briefly describes how Imatest™ measures them— with links to detailed pages. It is a guide to Imatest organized by image quality factors. Other guides include the Tour (organized by module) and Imatest documentation (the Table of Contents).
To illustrate the quality factors, we use this early morning image of Monument Valley from Hunt’s Mesa, near the Arizona-Utah border.
Image quality measurements are affected by the
- Lens — Imatest cannot measure lenses by themselves, but lenses can be effectively compared to one another using a single camera body with consistent image processing settings.
- Sensor — Imatest can measure the performance of the Lens+sensor from minimally-processed RAW images if they are available. Sharpness, distortion, vignetting, Lateral Chromatic Aberration, noise, and dynamic range are the principal factors that can be measured at this stage. Most of these measurements can be clearly classified as good/bad.
- Image processing pipeline— typically includes demosaicing, color correction, white balance, application of gamma and tonal response curves, sharpening, and noise reduction. Measured from the image delivered to the user (such as in-camera JPEG images). Additional image quality factors include tonal response (contrast, etc.), color response, and many others. The output of the pipeline may be compared to the minimally-processed lens+sensor measurements.The effect of the pipeline on subjective image quality can be highly scene- and application-dependent, making it difficult to assign “good” or “bad” rankings. Imatest results for these factors need to be interpreted carefully. Examples:
- Higher contrast images often score higher in visual quality assessment tests, but high contrast can cause clipping (visible as burnt-out highlights) in contrasty (often sunlit) scenes. Tonal response curves with “shoulders” can help. See Stepchart and Multicharts.
- Most consumers find accurate color to be boring, so camera manufacturers “enhance” colors in a number of ways, such as boosting chroma. See Colorcheck and Multicharts.
- Most consumers dislike noisy images, but software noise reduction (typically lowpass filtering in areas that lack contrasty features) can remove fine texture, resulting in a cartoon-like “plastic” skin appearance. See Log F-Contrast and Random/Dead Leaves.
Summary table
This table summarizes the image quality factors and links to pages where they are described in detail. Most of the charts are available from Imatest Store.
Quality factor | Chart | Module | Comments |
Camera, lens | |||
Blemishes, Sensor defects | Plain, uniformly-illuminated surface (flat field) | Blemish Detect | Can be displayed on flat screen monitor with Screen Patterns and opal diffusing glass. Note [1] |
Color accuracy | X-Rite ColorChecker (24-patch) | Colorcheck, Multicharts, Multitest | |
IT8.7 | Multicharts, Multitest | ||
ColorChecker SG, general mxn grids, and many other charts | Multicharts, Multitest | Note [1] | |
Dynamic range (DR), Tonal response, Contrast | Grayscale step charts | Stepchart, Multicharts, Multitest | Transmission charts such as the Imatest 36-Patch Dynamic Range chart or the Stouffer T4110 recommended for DR. Algorithm |
Reflective step charts (also works with transmissive charts) | Dynamic Range | Postprocessor for Stepchart, Multitest. Calculates DR by combining several analyses at different exposures. Doesn’t require a transmission chart. | |
Special charts: ISO-16067-1, QA-62, EIA Grayscale, ISO-14524 OECF, ISO-15739 Noise | Stepchart, Multicharts, Multitest | Note [1]. Many are available from the Imatest Store. | |
ColorChecker, ColorChecker SG, IT8.7, Step Charts | Multicharts, Multitest | ||
SFRplus, ISO 12233:2014 E-SFR | SFRplus, eSFR ISO | SFRplus does not measure DR. eSFR ISO measures ISO 15739 DR. Highly automated. Measures several factors. Available from the Imatest Store. | |
Exposure accuracy | Step charts (reflective) | Stepchart, Multicharts, Multitest | |
X-Rite ColorChecker | Colorcheck, Multicharts, Multitest | ||
ISO Sensitivity (closely related to Exposure Index) | Step charts | Stepchart | Two ISO sensitivity measurements are displayed when incident light (lux) is entered. Details in ISO Sensitivity and Exposure Index |
Various color and step charts | Multicharts, Multitest | ||
SFRplus | SFRplus | ||
X-Rite ColorChecker | Colorcheck, Multicharts, Multitest | ||
Lateral chromatic aberration | Slanted edge, ISO 12233 charts | SFR | Available from the Imatest Store. Note [2] |
SFRplus, ISO 12233:2014 E-SFR, Checkerboard | SFRplus, eSFR ISO, SFRreg, Checkerboard | Available from the Imatest Store. Note [2] | |
Dot pattern | Dot Pattern | Available from the Imatest Store. Note [2] | |
Lens distortion | Square or rectangular grid or checkerboard, | Distortion | Printable by Test Charts or displayed on LCD flat screen monitor with Screen Patterns. |
SFRplus, ISO 12233:2014 E-SFR | SFRplus, eSFR ISO, Checkerboard | Highly automated. Measures several factors. Results in the Image & Geometry display. | |
Dot pattern | Dot Pattern | Available from Imatest Store. | |
Light falloff, vignetting | Plain, uniformly-illuminated surface | Uniformity | Can be displayed on flat screen monitor with Screen Patterns. Opal diffusing glass recommended. |
Noise | Step charts | Stepchart | |
X-Rite ColorChecker | Colorcheck | ||
SFRplus | SFRplus | Measures flat areas near slanted-edges. Best with low (4:1) contrast charts. | |
eSFR ISO | eSFR ISO | Measures noise from grayscale surrounding center of chart. | |
Wide variety of grayscale stepcharts and color charts | Multicharts | Works with a large variety of grayscale and color charts if patches are large enough. Can measure sensor (raw) noise. | |
Sharpness (MTF) | Slanted-edge, ISO 12233 | SFR, Rescharts | ISO 12233:2000 and 2014 charts available from Imatest Store. Edges printable by Test Charts. Algorithm |
SFRplus, eSFR ISO, SFRreg, Checkerboard | SFRplus, eSFR ISO, SFRreg, Checkerboard | Highly automated. Measures several factors. Available from Imatest Store. | |
Other charts: Star, Spilled Coins, Wedge, etc. | Rescharts, Star, Log F-C, Random, Wedge… | Both interactive and fixed modules. Each responds differently to signal processing. | |
Texture detail | Log F-Contrast, Spilled Coins (Dead Leaves) | Log F-Contrast Random/Dead Leaves | |
Lens flare (Veiling glare) | Reflective Q-13 or Q-14 step chart with “black hole” | Stepchart | See Veiling Glare. Note [1] |
Color moiré | Log Frequency | Log Frequency, Wedge | |
Artifacts | Log F-Contrast Any arbitrary image | Log F-Contrast SSIM | Notes [1,2] SSIM measures degradation due to image processing (primarily compression) by comparing two images: reference and processed. |
Prints | |||
Dmax (deepest black tone) | Custom test chart printed from file, scanned on profiled flatbed scanner | Print Test | Gamutvision extracts these properties from ICC profiles. |
Color gamut |
Notes: [1] Not available in Imatest Studio. Available in Master, Image Sensor, etc. [2] can be printed from Test charts, but we recommend purchasing it from the Imatest Store.
Links
The RIT Center for Imaging Science has done some excellent work, but links that used to be on their site are hard to find. Some missing links: Direct Digital Image Capture of Cultural Heritage from RIT is a gold mine of information. Links to a number of reports on image quality targeted at museums and cultural institutions. The 78-page Final Project Report by Berns, Frey, Rosen, Smoyer and Taplin, July 2005, is probably the best summary unless you have time for Erin P (Murphy) Smoyer’s 345 page Master’s thesis (about twice the length of the average Ph.D. thesis).
The Research Library Group (RLG) has some useful documents such as Guides to Quality in Visual Resource Imaging (2000). These articles are the predecessors to the above-mentioned RIT Direct Digital Image Capture work.
Paul van Walree has an excellent page on Optics, covering several sources of degradation.
The University of Texas Laboratory for Image & Video Engineering is doing some interesting work on image and video quality assessment, which approaches the problem using information theory, natural scene statistics, wavelets, etc. Challenging material!
Details of several Imatest algorithms are included in Appendix C, Video Acquisition Measurement Methods (pp. 91-125), of the Public Safety SoR (Statement of Requirements) volume II v 1.0, released by SAFECOM, prepared by ITS (a division of NTIA, U.S. Department of Commerce). No credit is given, but the style and illustrations will be recognizable.