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Imatest Announces the WFOV Module

Imatest introduces its new Wide Field of View (WFOV) Module, which is an easy-to-use platform for testing sharpness in cameras with FOV up to 200º. This solution integrates with the Modular Test Stand and features three rail systems for easy positioning and mounting of camera devices, peripheral test targets, and Kino Flo LED panels. The main chart holder accommodates a variety of different test charts; mounting points for Isolight Pucks enable easy measurement of lighting brightness and color uniformity. (more…)

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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…)

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Seoul, South Korea – Imatest Training Course – October 20-21, 2020

Imatest in Seoul

Imatest engineers will visit Seoul, October 20-21, 2020, to offer a paid two-day training course (October 20-21) to professionals using or considering Imatest software to improve their image quality testing processes. A free information seminar will be offered on October 19. 

Seoul 2020 training image

Two-Day Training Course

image (2)

The training course offers attendees insight into the capabilities of Imatest software in both research and development and manufacturing environments.

After taking this course, you will have:

  • An understanding of key image quality factors
  • Practical knowledge of how to apply Imatest software to measure the factors
  • An overview of how to set up and tailor your test lab for accurate measurements

It is highly recommended you have a basic understanding of how cameras work (see recommended prerequisites). A detailed training schedule is also available.

Date and Time

October 20-21, 2020
09:00 – 18:00, depending on the questions.

Location Details

TBD

Instructor

TBD

Sign up online or contact a reseller in your area.

Register for Training

Free Information Seminar

If you are interested in finding out more about how Imatest software can improve your image quality testing, we encourage you to come to our free information seminar.

Time

October 19, 2020
Time TBD

Location

TBD

Please register if you are interested in attending. We look forward to meeting you in person.

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Imatest Announces Modular Test Stand

Boulder, Colorado, August 30, 2019—Imatest, a global provider of image quality testing solutions, now offers a Modular Test Stand (MTS) that enables you to produce superior cameras while significantly reducing time spent in the lab. (more…)

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July 2019 Newsletter

Our newsletter features our products, company news, educational image quality articles, Imatest events, and relevant industry articles. Subscribe to receive our newsletters in your inbox. (more…)

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June 2019 Newsletter

Our newsletter features our products, company news, educational image quality articles, Imatest events, and relevant industry articles. Subscribe to receive our newsletters in your inbox.

Imatest-Furonteer Partner to Reduce Geometric Camera Calibration Time

Imatest and Furonteer Reduce Camera Instrinsic Calibration Time

Imatest and Furonteer partnered in early 2019 to provide high throughput production machines for geometric calibration of single and multicamera devices.

 

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Imatest software testing program for early access - Pilot Program

Join our Pilot Program

A new Imatest software release is coming soon. Join our pilot program for early access to the new version in testing.

 

Join Now

(more…)

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Shanghai, China – Imatest Training Course – November 11-12, 2020

Imatest in Shanghai

Imatest engineers will visit Shanghai, China, November 11-12, 2020, to offer a paid two-day training course to professionals using or considering Imatest software to improve their image quality testing processes. A free information seminar will be offered on November 10.

Shanghai 2020 training image

Two-Day Training Course

image (2)

The training course offers attendees insight into the capabilities of Imatest software in both research and development and manufacturing environments.

After taking this course, you will have:

  • An understanding of key image quality factors
  • Practical knowledge of how to apply Imatest software to measure the factors
  • An overview of how to set up and tailor your test lab for accurate measurements

It is highly recommended you have a basic understanding of how cameras work (see recommended prerequisites). A detailed training schedule is also available.

Date and Time: November 11-12, 2020; 09:00 – 18:00, depending on the questions.

Location Details: TBD

Instructor: Henry Koren, Director of Engineering, Imatest

Registration: Contact a reseller in your area or cick the registration button below.

Register for Two-Day Training

Free Information Seminar

If you are interested in finding out more about how Imatest software can improve your image quality testing, we encourage you to come to our free information seminar.

Date and Time: November 10, 2020; time: TBD

Location: TBD

Register for Free Information Seminar

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Seoul, South Korea – Imatest Training Course – October 20-21, 2020

Imatest in Seoul

Imatest engineers will visit Seoul, October 20-21, 2020, to offer a paid two-day training course (October 20-21) to professionals using or considering Imatest software to improve their image quality testing processes. A free information seminar will be offered on October 19. 

Seoul 2020 training image

Two-Day Training Course

image (2)

The training course offers attendees insight into the capabilities of Imatest software in both research and development and manufacturing environments.

After taking this course, you will have:

  • An understanding of key image quality factors
  • Practical knowledge of how to apply Imatest software to measure the factors
  • An overview of how to set up and tailor your test lab for accurate measurements.

It is highly recommended you have a basic understanding of how cameras work (see recommended prerequisites). A detailed training schedule is also available.

Date and Time: October 20-21, 2020; 09:00 – 18:00, depending on the questions.

Location Details: TBD

Instructor: Henry Koren, Director of Engineering, Imatest

Registration: Contact a reseller in your area to register for this two-day course or click the registration button below.

Register for Two-Day Training

Free Information Seminar

If you are interested in finding out more about how Imatest software can improve your image quality testing, we encourage you to come to our free information seminar.

Date and Time: October 19, 2020; Time is TBD

Location: TBD

Register for Information Seminar

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San Jose, CA – Imatest Training Course – August 6-7, 2020

Imatest in San Jose

Imatest engineers will visit San Jose, California between August 6-7, 2020 to host a paid two-day training course to professionals using or considering Imatest software to improve their image quality testing processes.

Image Quality Testing Training with Imatest on August 6-7, 2020

Two-Day Training Course

image (2)

The training course offers attendees insight into the capabilities of Imatest software in both research and development and manufacturing environments.

After taking this course, you will have:

  • An understanding of key image quality factors
  • Practical knowledge of how to apply Imatest software to measure the factors
  • An overview of how to set up and tailor your test lab for accurate measurements.

It is highly recommended you have a basic understanding of how cameras work (see recommended prerequisites). A detailed training schedule is also available.

Date and Time: August 6-7, 2020; 09:00 – 18:00 (depending on questions)

Location Details: TBD

Instructor: TBD

Register for Two-Day Training

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Germany – Imatest Training Course – March 24-25, 2020

Imatest engineers planned to visit Germany on March 24-25, 2020 to host a paid two-day training course to professionals using or considering Imatest software to improve their image quality testing processes.

In light of the COVID-19 Coronavirus, this training course will be held remotely.

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Correcting nonuniformity in slanted-edge MTF measurements

Slanted-edge regions can often have non-uniformity across them. This could be caused by uneven illumination, lens falloff, and photoresponse nonuniformity (PRNU) of the sensor. 

Uncorrected nonuniformity in a slanted-edge region of interest can lead to an irregularity in MTF at low spatial frequencies. This disrupts the low-frequency reference which used to normalize the MTF curve. If the direction of the nonuniformity goes against the slanted edge transition from light to dark, MTF increases. If the nonuniformity goes in the same direction as the transition from light to dark, MTF decreases. 

To demonstrate this effect, we start with a simulated uniform slanted edge with some blur applied.

Then we apply a simulated nonuniformity to the edge at different angles relative to the edge. This is modeled to match a severe case of nonuniformity reported by one of our customers:

 

Here is the MTF obtained from the nonuniform slanted edges:

If the nonuniformity includes an angular component that is parallel to the edge, this adds a sawtooth pattern to the spatial domain, which manifests as high-frequency spikes in the frequency domain. This is caused by the binning algorithm which projects brighter or darker parts of the ROI into alternating bins.

 

Compensating for the effects of nonuniformity

Although every effort should be made to achieve even illumination, it’s not always possible (for example, in medical endoscopes and wide-FoV lenses).

Imatest 4.5+ has an option for dealing with this problem for all slanted-edge modules (SFR and Rescharts/fixed modules SFRplus, eSFR ISO, SFRreg, and Checkerboard). It is applied by checking the “Nonuniformity MTF correction” checkbox in the settings (or “More” settings) window, shown on the right.

When this box is checked, a portion of the spatial curve on the light side of the transition (displayed on the right in Imatest) is used to estimate the nonuniformity. The light side is chosen because it has a much better Signal-to-Noise Ratio than the dark side. In the above image, this would be the portion of the the edge profile more than about 6 pixels from the center. Imatest finds the first-order fit to the curve in this region, limits the fit so it doesn’t drop below zero, then divides the average edge by the first-order fit. 

The applied compensation flattens the response across the edge function and significantly improves the stability of the MTF:

Summary

For this example, Imatest’s nonuniformity correction reduces our example’s -26.0% to +22.8% change in MTF down to a -3.5% to +4.7% change. This is an 83% reduction in the effect of the worst cases of nonuniformity.

MTF50 versus nonuniformity angle without [blue] and with [orange] nonuniformity correction

While this is a large improvement, the residual effects of nonuniformity remain undesirable. Because of this, we recommend turning on your ISP’s nonuniformity correction before performing edge-SFR tests or averaging the MTF obtained from nearby slanted edges with opposite transition directions relative to the nonuniformity to reduce the effects of nonuniformity on your MTF measurements further.

Detailed algorithm

We assume that the illumination of the chart in the Region of Interest (ROI) approximates a first-order function, L(d) = k1 + k2d, where d is the horizontal or vertical distance nearly perpendicular to the (slanted) edge. The procedure consists of estimating k1 and k2, then dividing the linearized average edge by L(d). 

k1 and k2, are estimated using the light side of the transition starting at a sufficient distance dN from the transition center xcenter, so the transition itself does not have much effect on the k1 and k2 estimate. To find dN we first find the 20% width d20 of the line spread function (LSF; the derivative of the edge), i.e., the distance between the points where the LSF falls to 20% of its maximum value. 

dN = xcenter + 2 d20 

If the edge response for x > dN has a sufficient number of points, it is used to calculate k1 and k2 using standard polynomial fitting techniques. The result is a more accurate representation of the edge with the effects of nonuniformity reduced.

Future work

  • Consider the 2D nonuniformity across the ROI before sampling the 1D average edge
  • Use an image of a flat-field to perform nonuniformity correction within Imatest
  • Consider the impact of noise which was not included in this study
  • Incorporate enhancements to the slanted-edge algorithms into future revisions of ISO 12233

 

For any questions on how to do this, or how we can help you with your projects, contact us at support@imatest.com.

 

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Greetings From the Path of Totality

If you were lucky enough to travel to the path of totality on Monday, August 21st, you know firsthand how incredible it is to suddenly experience twilight in the middle of the day. The sun transforms into a hole in the sky, casting eerie shades of purple and a 360º sunset on the clouds. Just minutes later, the sun rises over the moon, creating a diamond ring effect. Witnessing this astronomical spectacle in person can’t compare to the photos and descriptions, but the images that I captured in Kearney, Nebraska are truly remarkable! Fewer than 1 in 1,000 people ever have the chance to see the Sun’s atmosphere in their lifetime, and I am extremely grateful to be one of them!

My camera setup. Panasonic GH3 with Canon adapter and 55-250mm Canon lens. I made my own solar filter with film purchased from Spectrum Telescope. I forgot my tripod, so I had to use my gorilla pod.

Composite image from my time-lapse! Each snapshot is about 3 minutes apart.

Composite image of totality! The solar filter was removed during totality and then reapplied for the final phase.

“God’s diamond ring”

The solar corona, consisting of 2-million-degree plasma.

Timelapse 

Each frame was taken 3 seconds apart and play back is 24 frames per second. The solar filter was removed during totality and then reapplied for the final phase.

– Alex Schwartz, Video Production & Mechanical Engineering Intern

 

 

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Imatest Support for CPIQ Metrics

What is CPIQ?

IEEE-SA working group P1858 created the CPIQ standard. CPIQ seeks to standardize image quality test metrics and methodologies across the mobile device industry, correlate objective test results with human perception, and combine this data into a meaningful consumer rating system.
(more…)

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High Dynamic Range Target, ITI LED Lightbox

We are pleased to announce our new High Dynamic Range (HDR) test chart with a density range exceeding 120dB (optical density >6.0). This chart allows you to the measure the dynamic range, tonal response and noise of HDR cameras with a single image instead of multiple, exposure bracketed images. It also contains slanted edges for MTF measurements. (more…)

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SFRreg: SFR from Registration Marks

Imatest SFRreg performs highly automated measurements of sharpness (expressed as Spatial Frequency Response (SFR), also known as Modulation Transfer Function (MTF)) and Lateral Chromatic Aberration from images that contain registration mark patterns (circles with two light and two dark quadrants). Unlike standard test charts, these patterns do not need to be located on a flat (planar) surface. Depending on the image source, they offer two advantages. You can

  • Test images at infinity distance (or any distance of choice) using a compact projection system such as the Optikos Meridian camera test system.
  • Test the sharpness of extreme fisheye lenses (with angular fields of view over 180 degrees, whose MTF cannot be measured near the image boundaries with a single flat target) using an array test charts, each consisting of an individual registration mark. Registration mark charts, such as the one shown on the right, may be purchased from the Imatest store or printed on a high-quality inkjet printer. Since Region of Interest (ROI) selection is automatic, they may be positioned where needed. They work best when facing the camera.
registration_markRegistration mark

Details of the regions to be analyzed are based on user-entered criteria (similar to SFRplus or eSFR ISO, which it closely resembles).

Sharpness is derived from light/dark slanted edges inside the registration marks, as described in Sharpness: What is it and how is it measured? SFRreg can handle a wide range of camera aspect ratios and chart arrangements.

SFRreg operates in two modes.

  • Interactive/setup mode  allows you to select settings and interactively examine results in detail. Saved settings are used for Auto Mode.
  • Auto mode  runs automatically with no additional user input. ROIs are located automatically based on settings saved from the interactive/setup mode. This allows images of different sizes and framing to be analyzed with no change of settings. Auto mode works with large batches of files, and is especially useful for automated testing, where framing may vary from image to image.

Part 1 of the instructions introduces SFRreg and explains how to obtain and photograph the chart. Part 2 shows how to run SFRreg inside Rescharts and how to save settings for automated runs. Part 3 illustrates the results.

 

SFRreg images from the Optikos Meridian projection system

Imatest SFRreg is originally designed designed to work with images from the Optikos Meridian system, which consists of several projectors that project registration mark patterns towards a camera. These patterns appear at infinity focus at the camera. A typical image is shown below.

MERIDIAN-7-4K-e1423515004804

Optikos_9_proj_640WImage acquired from a 9-projector Optikos Meridian system

SFRreg images from arbitrary arrays of printed registration mark charts

SFRreg also works with printed registration mark patterns, which can be placed anywhere in the image. For extreme wide-angle (fisheye) lenses they should be oriented facing directly towards the camera. Here is a synthesized image (we’ll add a real one soon). You can add other charts— typically color or grayscale— to the image for additional measurements.

reg_marks_fisheye_fakeFisheye lens image with synthesized registration mark charts oriented facing the camera

SFRreg chart print options (can be selected when ordering)

  Options Notes
Media Inkjet (reflective),
LVT film (transmissive)
Inkjet (reflective) is usually the most practical choice.
Contrast
4:1, 10:1
4:1 contrast is specified in the new ISO 12233:2014 standard.
Surface Matte or semigloss Semigloss is slightly sharper, but is more susceptible to glare (specular reflections), especially with wide angle lenses. Matte surface is recommended for wide angle lenses or difficult lighting situations.

 

Slanted-edge algorithm The algorithms for calculating MTF/SFR were adapted from a Matlab program, sfrmat, written by Peter Burns () to implement the ISO 12233:2000 standard. Imatest SFR, SFRplus, SFRreg, and eSFR ISO incorporates numerous improvements, including improved edge detection, better handling of lens distortion, a nicer interface, and far more detailed output. The original Matlab code is available on http://losburns.com/imaging/software/SFRedge/index.htm. In comparing sfrmat results with Imatest, note that if no OECF (tonal response curve) file is entered into sfrmat, no tonal response curve is assumed, i.e., gamma = 1 (linear response). Since the default value of gamma in Imatest is 0.5, which is typical of digital cameras, you must set gamma to 1 to obtain good agreement with sfrmat.

Obtaining and photographing the charts

Registration Mark charts can be purchased from the Imatest store in a variety of inkjet media (reflective and transmissive) (Other media will be available on request.) Although we recommend that you purchase the charts, they can be printed on photographic-quality inkjet printers, but you must have fine materials, skill, and a knowledge of color management.

 

SFRreg results

When calculations are complete, results are displayed in the Rescharts window, which allows a number of displays to be selected. The following table shows where specific results are displayed. Results plots are very similar to SFRplus and eSFR ISO. We show two samples of results below.

sfrreg_display_selectionSFRreg display selections

Measurement Display
MTF (sharpness) for individual regions 1. Edge and MTF
MTF (sharpness) for entire image 4. Multi-ROI summary
12. 3D plot
13. Lens-style MTF plot
Lateral Chromatic Aberration 2. Chromatic Aberration
Original image showing region selection 8. Image & geometry
EXIF data 7. Summary & EXIF data
Acutance/SQF (Subjective Quality Factor) 3. SQF / Acutance
Edge roughness 14. Edge roughness
Chromatic Aberration (radial) 15. Radial (Chr Aber, etc.)

Multi-ROI summary display

 

sfrreg_multi_regionSFRreg results in Rescharts window: Multiple region (ROI) summary
(Only upper Vertical regions have been selected to keep the view uncluttered.)

The multi-ROI (multiple Region of Interest) summary shown in the Rescharts window (above) contains a detailed summary of SFRreg results. (3D plots also contain an excellent summary.) The upper left contains the image in muted gray tones, with the selected regions surrounded by red rectangles and displayed with full contrast. Up to four results boxes are displayed next to each region. The results are selected the the Display options area on the right of the window, below the Display selection.

The Results selection (right) lets you choose which results to display. N is region number. Ctr-corner distance % is the approximate location of the region. CA is Chromatic Aberration in area, as percentage of the center-to-corner distance (a perceptual measurement). A legend below the image shows which results are displayed.

The View selection (far right) lets you select how many results boxes to display, which can be helpful when many regions overlap. From top to bottom the number of boxes is 4, 3, 2, 2, and 1, respectively.


Results selection
View selection

Edge and MTF display

 

sfrreg_edge_MTFEdge and MTF display in Rescharts window
Diffraction-limited MTF and edge response are shown as a pale brown dotted lines
when pixel spacing (5.7um for the EOS-40D) has been entered.

This display is identical to the SFR Edge and MTF display. The edge (or line spread function) is plotted on the top and the MTF is plotted on the bottom. The edge may be displayed linearized and normalized (the default; shown), unlinearized (pixel level) and normalized, or linearized and unnormalized (good for checking for saturation, especially in images with poor white balance). Edge display is selected by pressing More settings.

There are a number of readouts, including 10-90% rise distance, MTF50, MTF50P (the spatial frequency where MTF is 50% of the peak value, differing from MTF50 only for oversharpened pulses), the secondary readouts (MTF @ 0.125 and 0.25 C/P in this case), and the MTF at the Nyquist frequency (0.5 cycles/pixel). The diffraction-limited MTF curve (not shown above) is displayed as a pale brown dotted line when pixel pitch is entered.

MTF is explained in Sharpness: What is it and how is it measured? MTF curves and Image appearance contains several examples illustrating the correlation between MTF curves and perceived sharpness.

 

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January 2015 Newsletter

Imatest is excited to announce our new Chrome on Glass Target sizes. We have increased our target selection from 2″ x 2″ Chrome on Glass SFRplus Targets to a variety of sizes and highly customizable solutions. The chrome on glass substrate provides extremely high resolution targets to satisfy a variety of testing needs. We offer larger targets for customers using high resolution cameras within compact testing systems, as well as extremely small targets for testing equipment like endoscopes and microscopes at varying magnifications.

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Imatest December 2014 Newsletter

Wishing all our customers, partners and resellers very happy holidays and a prosperous New Year. Imatest is offering 25% off all software support renewals through the end of the year.

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Imatest October 2013 Newsletter

Imatest 3.10 Released

The latest version of Imatest has been optimized for speed and includes many improvements and new features. A new image stabilization module allows users to test the efficacy of a camera’s optical image stabilization (OIS). To see a rundown of all of the new additions to version 3.10, take a look at our blog detailing the release. (more…)

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December 2012 Newsletter

Imatest 3.9 Released

36-Patch Dynamic RangeNew features include:

  • Support for high-speed manufacturing testing in the Imatest IT version
  • Flat screen display testing via an improved Blemish Detect module
  • Dynamic range testing with our new high precision transmissive 36 patch chart
  • More robust SFRplus automated region detection, and improved Field of View and geometrical measurements

(more…)

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Slanted-Edge SFR Saturation

The following (Rescharts) SFRplus results shows the edge (unnormalized) and MTF results for one region near the center of the image that has the green channel saturated. (We deliberated boosted the image to saturate it.) The green channel is very clearly saturated, but luminance doesn’t quite reach saturation because of the low level of the blue channel. Note the sharp corner where the green channel reaches saturation. This corner has quite a lot of high frequency energy that is responsible for the high MTF of the green channel: MTF50 = 435 LW/PH, about 15-20% higher than the other channels.

SFRplus results showing how saturated green channel (red arrow illustrates onset) affects MTF

Measuring the impact of saturation is not easy because information is actually lost in the saturated region, i.e., you can’t tell exactly what you’d have gotten if the system were linear, and it’s difficult to make a reliable estimate of the corner sharpening caused by saturation, which is responsible for the MTF boost. So the metric we’ve chosen is

  • the fraction of the average edge above 0.99 (99% of the maximum value) for the edge with the largest fraction, or
  • the fraction of the average edge below 0.02 (2% of the maximum value) for the edge with the largest fraction.

These are about the best numbers I’ve been able to come up with to measure the severity of clipping, and I believe they are usable for pass/fail criteria. (the pass/fail threshold would be somewhere between 0.3 and 0.7).

Results

Here are results from the JSON output.

“sat_description”: “extreme edge max, edge min, fractions >.95, >.98, >.99, <.05, <.02″,

This is a description of the results in satsumall (saturation summary for all regions), below.

  1. The maximum value for all edges (20 in this analysis) for all colors (R, G, B, Y, where it can never be in the Y-channel because Y = 0.3*R + 0.59*G + 0.11*B.
  2. The minimum value for all edges.
  3. The largest fraction of pixels above the center value ((max+min)/2) for all edge regions and all colors where the pixel level is above 0.95 of the maximum pixel level (255 for 8-bit systems).
  4. The largest fraction of pixels above the center value where the pixel level is above 0.98 of the maximum.
  5. The largest fraction of pixels above the center value where the pixel level is above 0.99 of the maximum.
  6. The largest fraction of pixels below the center value where the pixel level is above 0.05 of the maximum.
  7. The largest fraction of pixels below the center value where the pixel level is above 0.02 of the maximum.

“satsumall”: [1,0.0636,0.978,0.967,0.967,0,0],

These are the actual results, showing no low saturation and strong high saturation (e.g., 0.978 (97.8%) of the pixels above the center value are above 0.95 (95%) of the maximum value.

“mean_pixel_level_ctr_9th”: [0.7530514761],

This is the mean relative pixel level (fraction of the maximum level) for the central ninth (by area; 1/3 X 1/3 length) of the image. It is used in the SFR Setup window to indicate underexposure (when < 0.3) or overexposure (when > 0.8). These numbers would not necessarily be used for pass/fail.

Pass/fail results

To obtain pass/fail results for quadrants and saturation, the lines shown in boldface below (all optional) should be added to the pass/fail ini file. Comments shown in red are not a part of the file.

[sfrplus]

Chart_mean_pixel_level_bounds = .3 .8|
The lower and upper bounds of the chart mean normalized pixel level (for the central 1/9 = 1/3 X 1/3 linearly) of the chart.
Low_pixel_saturation_fraction_max = .3

High_pixel_saturation_fraction_max = .3

Chart_radial_pixel_shift_max = 15

Here is the corresponding JSON pass/fail result, with many lines omitted.

“passfail”: {

            “High_pixel_saturation_fraction_max”: [0.3],
            “High_pixel_saturation_fraction”: [0.967032967],
            “High_pixel_saturation_fraction_passed”: [0],
            “Low_pixel_saturation_fraction_max”: [0.3],
            “Low_pixel_saturation_fraction”: [0],
            “Low_pixel_saturation_fraction_passed”: [1],
            “Chart_mean_pixel_level_bounds”: [0.3,0.8],
            “Chart_mean_pixel_level”: [0.7530514761],
            “Chart_mean_pixel_level_passed”: [1],

           …
        }

 
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