The Pass/Fail monitor (introduced In Imatest 4.0) provides a real-time indication of whether a device has passed or failed a test. It saves the trouble of digging through results— in figures or CSV or JSON files. Key features: It can stay open while modules run, displaying results immediately after calculations are complete. It works best on systems with a high resolution screen or dual screens. It interfaces with most Imatest analysis modules. It can be extremely valuable for developing and testing Pass/Fail criteria for Imatest IT (Industrial Testing). It can call several utilities for helping with this process. It displays […]

Introduction Part 1 of this page illustrates images analyzed in Random Scale-invariant & Dead Leaves. The images are not shown original size; they’ve been resized to be approximately equal in magnification with respect to the original chart image— with enough magnification to show the results of the camera optics and image processing. Part 2 demonstrates how demosaicing is the cause of a commonly observed discrepancy between Spilled Coins and slanted-edge MTF measurements. Part 1: Images used in Random / Dead Leaves Original pattern (cropped from the middle of the chart), for reference. Original pattern (reduced from file used to print […]

Introduction: Starting in version 4.5, Imatest is capable of performing the cross-correlation based texture blur measurement which is under consideration for ISO 19567-2: Texture Analysis on Stochastic Pattern. This is a texture-blur-analysis method originally proposed in Description of texture loss using the dead leaves target: Current issues and a new intrinsic approach by Kirk et al at Image Engineering.  This method starts from the same principles as the so-called “Direct” method of Cao et al which is the Power Spectral Density-based method described on the Random Module page. The main difference is the Direct method makes use of assumed statistical properties […]

This document contains reference data intended to help Imatest users implement test plans that include automatically-detected slanted-edge modules. It describes the most important JSON results, which can be used for Pass/Fail criteria, as well as the key settings needed to get these results.Settings windows and recommended settings Settings for slanted-edge modules Slanted-edge modules can be run in either Setup (interactive) or Auto (batch-capable) mode. You can make settings in Setup mode; Auto mode uses saved settings from Setup mode.  When you run one of  the four auto-detection slanted-edge SFR modules (eSFR ISO, SFRplus, Checkerboard, and SFRreg) in Setup mode, the […]

Overview Imatest modules can perform basic analysis of a video system’s ability to auto focus (AF), auto white balance (AWB) or auto expose an image (AE). Combined, these three tests may be referred to as AAA analysis. Currently, temporal analysis is only compatible with the following modules: Auto Focus: SFR Mean Normalized Pixel Level (Auto Exposure): Arbitrary Charts, CMP DT003, Colorchecker 24, Colorchecker SG, ColorGuage 6×5, RezChecker 6×7, Contrast-Resolution, ChromaDuMonde 28, DreamCatcher 48, EIA Grayscale, 36 Patch Dynamic Range, ISO 14524, ISO 15739, IT8.7, ITEGrayscale, OECF 20, QA-61, QA-62, QA79, QP Card, SpyderCHECKR, TE226, TE269 Exposure Error (Auto Exposure): CMP […]

Test Charts creates test chart files for printing on high quality inkjet printers. This page focuses on Scalable Vector Graphics (SVG) charts, many of which are used for measuring sharpness (MTF) with Imatest SFR, SFRplus, eSFR ISO, Checkerboard, and SFRreg. (Bitmap charts are described elsewhere.) SVG charts can be printed any size at a printer’s maximum quality (i.e., resolution) with no limitations, and they generally require much less storage than bitmap images. The SVG charts designed for automated testing with SFRplus and eSFR ISO (based on ISO 12233:2014/2017) have numerous advantages over the familiar but obsolete ISO 12233:2000 chart. Most […]

Page Contents This page provides an overview of the summary metrics Overview Level-Based Metrics Count-Based Metrics Minimum Measurable Stray Light Maximum Measurable Stray Light Overview Similar to how MTF50 (SFR50) and MTF area provide a single number for resolution, stray light also has single number measurements for characterizing stray light performance. These summary metrics fall into two categories: Level-Based: Metrics that are about the amount (level) of the stray light Count-Based: Metrics about the number of pixels (count) that meet a criteria Level-Based Metrics Overview Level-based summary metrics describe the amount (level) of stray light in the image. They include […]

This page describes the technical considerations of stray light testing. Test Assumptions The table below describes assumptions that may be made for stray light testing, along with the associated consequences (if the assumption is not entirely true) and possible improvements to address the consequences. Light Source Collimated vs Diverging Source From a calculation perspective, stray light may be measured with either a diverging or collimated light source. However, for repeatability between test setups, a collimated light source is recommended.  Two aspects over which stray light may be measured are the angle of rays and their intersection (translation) relative to the […]

Page Contents This is the landing page for Imatest’s stray light documentation. This page provides an introduction to stray light and how to test for stray light using the small, bright light source approach. It also introduces the concept of “normalized stray light metric images”. See also the Veiling Glare documentation for information about the chart-based approach to measuring veiling glare; a specific form of stray light.  Intro to stray light (flare) How to test for stray light Test environment Light source, set up, and alignment Test coverage: extent and sampling Image data Normalized stray light metric images Normalized stray […]

 Analyze the Siemens Star chart New in Imatest 2020.1 (Feb. 2020)  Shannon information capacity can be calculated from images of the Siemens star, with much better accuracy than slanted-edges. The old slanted-edge method has been deprecated.   The white paper, “Camera information capacity: a key performance indicator for Machine Vision and Artificial Intelligence systems“, which briefly introduces information theory, describes the camera information capacity measurement, then shows results (including the effects of artifacts) is now available for download. Imatest 5.0: Half-stars (rotated by multiples of 45º) can now be analyzed. A star-only pattern (without density patches, etc.) can be selected in […]

Analysis of random scale-invariant patterns, including the Spilled Coins (Dead Leaves) Pattern, for measuring texture sharpness Introduction – Obtaining – Photographing – Running – Automatic ROI detection – Output  MTF – MTFnn, MTFnnP – Power Spectral Density – Equations & Scale-invariance Related pages:  Texture examples – Dead Leaves measurement issue – Random/Dead Leaves cross method      Introduction  Random/Dead Leaves, which runs under the interactive Rescharts interface or as a fixed (non-interactive, batch-capable) module, measures SFR (Spatial Frequency Response) or MTF (Modulation Transfer Function) from random scale-invariant (or approximately scale-invariant) test charts, including “Dead Leaves” and “Spilled Coins” charts. It is primarily used to measure the effects of signal processing on image texture. […]

A comparison of sensitivity to signal processing: Results for additional cameras This page contains additional Slanted-edge, Siemens Star, and Log F-Contrast results for four cameras, in support of claims in Slanted-edge versus Siemens Star that Siemens Star MTF measurements are nearly as sensitive to sharpening as low-contrast (4:1) slanted-edge measurements. The Siemens Star’s high contrast (specified at >50:1) makes it quite sensitive to saturation and to “shoulders” (regions of reduced contrast) in camera tonal response. Slanted-edge MTF measurements are stable, reliable, and more representative of perceived image sharpness under a wide range of conditions (in addition to their many well-known […]

A comparison of sensitivity to signal processing In this page we address concerns about the sensitivity of slanted-edge patterns to signal processing, especially sharpening, and we correct the misconception that sinusoidal patterns, such as the Siemens star, are insensitive to sharpening, and hence provide more robust and stable MTF measurements. The Siemens Star is of particular interest because, along with the slanted-edge, it is included in the ISO 12233:2014 standard.  To summarize our results, we found that sinusoidal patterns are sensitive to sharpening, though often less so than low contrast (4:1) slanted-edges. The relatively high contrast of the Siemens Star […]

Instructions and comments We are updating this page for the latest Skype/Lync specification. An index of of the Skype/Lync specifications can be found on  http://technet.microsoft.com/en-us/lync/gg278181.aspx. This document contains instructions for using Imatest with the Skype Hardware Certification Specification — For all Skype Video Devices Version 5.0. It also contains comments and suggestions (some of which we hope might be adopted in a future release of the spec). The Skype spec uses only a tiny fraction of Imatest’s powerful capabilities. To learn more, see Image Quality Factors and SFRplus (which allows many factors to be measured from a single image). In […]

Instructions and comments Under development We are updating this page for the latest Skype for Business Video Capture Specification, December 2016. An index of of the Skype/Lync specifications can be found on https://technet.microsoft.com/en-us/office/dn788953 This document contains instructions for using Imatest with the Skype for Business Video Capture Specification, which has two versions: personal solutions (Document Number: H100693) and conferencing devices (Document Number: M1023160), published December 2016. “Skype for Business V3.0” appears on a watermark, and 3.0 is indicated in the Revision History (Section 1). It also contains comments and suggestions for running Imatest. The Skype spec uses only a tiny […]

Introduction – Examples – Oversharpening and Undersharpening  Examples – Unsharp masking (USM) – Links   Introduction to sharpening Sharpening is an important part of digital image processing. It restores some of the sharpness lost in the lens and image sensor. Every digital image intended for human viewing benefits from sharpening at some point in its workflow— in the camera, the RAW conversion software, and/or the image editor. Sharpening has a bad name with some photographers because it has been overdone in some cameras (mostly low-end compacts and camera phones), resulting in ugly “halo” effects near edges. But it’s entirely beneficial when done properly. The JPEG image output […]

Photographic scientists and engineers stress the fact that no single number satisfactorily describes the ability of a photographic system to reproduce the small-scale attributes of the subject —Leslie Stroebel,John Compton, Ira Current, Richard Zakia Basic Photographic Materials and Processes, Second edition, p. 273 (Micro-image evaluation chapter), Focal Press, 2000 News: Imatest 23.1 contains a new method for calculating the information capacity from slanted-edge patterns, which has been developed and presented in the white paper,  “Measuring Camera Information Capacity with Imatest“. The slanted-edge method is faster and more efficient than the Siemens star method, but not as good for measuring artifacts […]

For more information on how to use INI files in Imatest IT, we recommend the Imatest INI File Reference This document was created by running sfrreg in Imatest 5.2.0. ALPHA on 31-May-2019 14:48:43. For Imatest IT, most of these entries don’t need to be entered. Many don’t affect Imatest IT results: they control interactive figure displays or figure output formats (figures are often not used in Imatest IT). Background Meaning Yellow Yellow background: Important to Imatest IT. Parameter and Description are in boldface. [IT] Cyan Cyan background: Figure settings. (Figures are used infrequently for IT.) [f] Gray Gray background: For […]

These posts describe several topics, including: SFRplus Quadrant analysis (it includes the center region as well), Saturation analysis, which attempts to estimate the severity of saturation in slanted-edge regions (ROIs), and a few other recent additions (November 2012). Saturation is important because saturated light or dark regions will result in artificially high MTF readings. How to select regions at a fixed distance from center to corner (typically in the range of 65-85%)

For more information on how to use INI files in Imatest IT, we recommend the Imatest INI File Reference For Imatest IT, most of these entries don’t need to be entered. Many don’t affect Imatest IT results: they control interactive figure displays or figure output formats (figures are often not used in Imatest IT). Background Meaning Yellow Yellow background: Important to Imatest IT. Parameter and Description are in boldface. [IT] Cyan Cyan background: Figure settings. (Figures are used infrequently for IT.) [f] Gray Gray background: For interactive operation. No effect on IT. Clear Clear background: Results details (units, scaling, etc.) […]