Running Rescharts slanted-edge modules (Interactive and Auto mode settings) Imatest Rescharts slanted edge modules— SFRplus, eSFR ISO, SFRreg, and Checkerboard— perform highly automated measurements of several key image quality factors using specially-designed test charts. This document shows how to run these modules in Rescharts and how to save settings for automated runs.  Four introductory pages —  SFRplus, eSFR ISO, SFRreg, and Checkerboard — describe each module and explain how to obtain and photograph the chart.  Rescharts Results Part 3 and Part 4 illustrate the results. Selecting files – Setup window – ROI selection & analysis – Edge ID files – Speeding up runs […]

Interactive Analysis of Resolution-Related Charts New in Imatest 2020.1 : Shannon information capacity from Siemens Star charts  Introduction – Supported charts – SFR – SFRplus – eSFR ISO – SFRreg – Checkerboard Getting Started – Rescharts Window  –   Rescharts modules Slanted-edge SFR – SFRplus – Log frequency (simple) – Log frequency-contrast – Star – Wedge  Random/Dead Leaves – Focus Score Introduction Imatest™ Rescharts is a highly-interactive interface for running several Imatest modules that can analyze images of several different test charts for resolution-related parameters such as sharpness (i.e., Spatial Frequency Response SFR, which is equivalent to Modulation Transfer Function MTF), color moiré, and fine detail lost to software noise reduction. All Rescharts modules can […]

Measure visible sensor defects The Human Visual System – Algorithm – Instructions – Settings window – Filtering and threshold – Display options – Defective pixels – Tuning – Results Flatfield Blemish Detect detects visible sensor defects (typically blurred (dark) spots caused by dust in front of the image sensor, but light blemishes can also be detected). To ensure that only visible blemishes are flagged— and blemishes below the threshold of visibility are not— the image is filtered by a response function derived from the Human Visual System (HVS). Filter settings are adjustable for a wide range of applications and viewing conditions.  The IT version of […]

Imatest eSFR ISO results Imatest eSFR ISO performs highly automated measurements of several key image quality factors using one of three versions of the ISO 12233:2017 Edge SFR chart: Standard, Enhanced, or Extended or the Extended ISO 12233:2023 . Unlike most other modules, the user never has to manually select Regions of Interest (ROIs). Image quality factors include Sharpness, expressed as Spatial Frequency Response (SFR), also known as the Modulation Transfer Function (MTF), Noise, measured from the grayscale patches surrounding the center of the chart, includes all types of noise calculated by Color/Tone Interactive and Color/Tone Auto (standard pixel noise, […]

Running eSFR ISO – Rescharts eSFR ISO – eSFR ISO setup window – Speeding up – More Settings window – Secondary Readouts – Gamma – Auto mode settings – Warnings – eSFR ISO summary Running eSFR ISO Imatest eSFR ISO performs highly automated measurements of several key image quality factors using one of three versions of the ISO 12233:2017 Edge SFR chart: Standard, Enhanced, or Extended or the Extended ISO 12233:2023 Edge SFR chart. This document shows how to run eSFR ISO in Rescharts and how to save settings for automated runs. Part 1 introduced eSFR ISO and explained how […]

Two operating modes – Charts –  ISO 12233:2017 Compliance – Advantages  Imatest eSFR ISO performs highly automated measurements of several key image quality factors using versions of the ISO 12233:2017 E-SFR (Edge SFR) and new ISO 12233:2023 E-SFR test charts that may be purchased from the Imatest store (recommended) or printed on a high-quality inkjet printer. Region of Interest (ROI) selection is automatic, based on user-entered criteria (similar to  SFRplus, which it closely resembles). Image quality factors include: Sharpness, expressed as Spatial Frequency Response (SFR), also known as Modulation Transfer Function (MTF) Lateral Chromatic Aberration Distortion  Simple low-order calculations; less accurate […]

Direct image acquisition allows images to be captured directly from a variety of devices without first being stored as files. It has several important applications. Introduction – Direct data reload for realtime analysis – Signal averaging By continuously reloading images, it can be used for realtime (or near-realtime) image analysis, where “realtime” means that analysis appears to be instant in the timeframe of human perception. It is especially valuable for focusing with slanted-edges (which can be analyzed faster than other MTF patterns) or with cropped areas of arbitrary images.   It is very useful for signal averaging — a technique […]

Imatest Checkerboard performs highly automated measurements of sharpness (expressed as Spatial Frequency Response (SFR), also known as Modulation Transfer Function (MTF)), Lateral Chromatic Aberration, and optical distortion from images of checkerboard patterns (with a recommended tilt angle of 2-7 degrees). The primary advantage of Checkerboard (as compared to Imatest’s other automatically-detected modules) is that it is relatively insensitive to framing. You can zoom in our out as much as you like, as long as there are detectable corner features.  This document illustrates Checkerboard results. Part 1 introduced Checkerboard and explained how to obtain and photograph the chart. Part 2 showed […]

Selecting files – Setup window – ROI selection & analysis area – Edge ID Files More settings window – Secondary Readout  – Settings area – Auto mode window Warnings – Clipping – Summary    Using Checkerboard Part 1 – Checkerboard patterns and how to photograph them Running Checkerboard (Interactive and Auto mode settings) Imatest Checkerboard performs highly automated measurements of sharpness (expressed as Spatial Frequency Response (SFR), also known as Modulation Transfer Function (MTF)), Lateral Chromatic Aberration , and optical distortion from tilted checkerboard images.The primary advantage of Checkerboard is that the field of view, i.e., the framing, does not need to be tied to the chart size (as it […]

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 the intersection (translation) of them relative […]

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. […]