Imatest was recently featured in Automoblog.net’s article, Three Companies Changing the Autonomous Driving Landscape. Carl Anthony writes:

“With driverless cars, the implication is huge because cameras will play a vital role in the forthcoming autonomous world. In order for autonomy to deliver on its promises of reducing collisions and traffic fatalities, image quality is essential. Imatest takes this into consideration as today’s automotive trends usher us further into autonomy.”

Read the full article at www.automoblog.net/2017/06/30/three-companies-changing-the-autonomous-driving-landscape/. 

Imatest is pleased to unveil updated documentation for Imatest IT. The documentation has been updated to include the latest software release (Imatest 4.5), including details for new features, filtering options for preferred languages, and several new Troubleshooting articles.

Users can now filter Imatest IT instructions for their preferred languages and interfaces including C, C++, Python, .NET (C# and Visual Basic), and EXE. In addition, there are now more detailed installation and setup instructions for both Windows and Linux versions.

Imatest IT ships with several example projects in C++, Python, C#, and Visual Basic. You can find them in the samples folder of your IT installation, along with example images of Imatest test charts that can be used for each of IT’s analysis modules.

Related Content

Automating Lab and Manufacturing Processes – [Webinar]

Imatest’s charts and software allow you, our users, to measure the characteristics and parameters of your imaging system. Quite often these measurements are used simply as metrics of image quality, to indicate the limits of the performance you can expect from your system or to predict the quality of the images it can take.

Some of the results Imatest can give you, however, are immediately actionable. Some results we supply can be used to directly improve the test image –and subsequent ones taken by the same system in the wild, of course–  by correcting the error which was measured. No new components need to be purchased, no judgement calls need to be made- sometimes the solution to a problem can be found with a mathematical model and a little computation. Once you measure such parameters with Imatest you can correct for them, thereby minimizing (or completely removing) their effect. This is an aspect of tuning the image processing pipeline, which is usually done by a dedicated Image Signal Processing (ISP) chip in a device to transform raw sensor data into an appropriate image. 

At Imatest, we informally call this “closing the loop”, because it completes the cycle from the camera-under-test to measurement and back to the camera (in the form of some adjustment). 

Today, we’re going to illustrate how to take radial distortion measurements from Imatest and use them to correct the distortion out of images taken with that camera (without buying a new lens). (more…)

This paper was given as part of the Electronic Imaging 2017 Image Quality and System Performance XIV and Digital Photography and Mobile Imaging XIII sessions.

When: Tuesday, January 31, 2017, at 12:10 pm

By: Robert Sumner with support from Ranga Burada, Noah Kram

Abstract: The dead leaves image model is often used for measurement of the spatial frequency response (SFR) of digital cameras, where response to fine texture is of interest. It has a power spectral density (PSD) similar to natural images and image features of varying sizes, making it useful for measuring the texture-blurring effects of non-linear noise reduction which may not be well analyzed by traditional methods. The standard approach for analyzing images of this model is to compare observed PSDs to the analytically known one. However, recent works have proposed a cross-correlation based approach which promises more robust measurements via full-reference comparison with the known true pattern. A major assumption of this method is that the observed image and reference image can be aligned (registered) with sub-pixel accuracy.

Read Full Paper:

Effects of misregistration on the dead leaves cross-correlation texture blur analysis

This paper was given as part of the Electronic Imaging 2017 Autonomous Vehicles and Machine session.

When: Monday, January 30, 2017, at 10:10 am

By: Norman Koren with support from Henry Koren, Robert Sumner

Abstract:  The ISO 16505 standard for automotive Camera Monitor Systems uses high contrast hyperbolic wedges instead of slanted-edges to measure system resolution, defined as MTF10 (the spatial frequency where MTF = 10% of its low frequency value). Wedges were chosen based on the claim that slanted-edges are sensitive to signal processing. While this is indeed the case, we have found that wedges are also highly sensitive and present a number of meas­ure­ment challenges: Sub-pixel location variations cause unavoidable inconsistencies; wedge saturation makes results more stable at the expense of accuracy; MTF10 can be boosted by sharpening, noise, and other artifacts, and may never be reached. Poor quality images can exhibit high MTF10. We show that the onset of aliasing is a more stable performance indicator, and we discuss methods of getting the most accurate results from wedges as well as misun­derstandings about low contrast slanted-edges, which cor­relate better with system performance and are more repre­sentative of objects of interest in automotive and security imaging.

Full Text: Measuring MTF with Wedges: Pitfalls and best practices

Slides: Wedge_measurements_N_Koren_2017

Imatest upgrades based on the paper

The recommended metric to replace MTF10 (min(MTF10, onset of aliasing, Nyquist frequency)) is displayed in the Wedge MTF plot as well as the (new in Imatest 5.0) Multi-Wedge plot, shown below.

Multi-Wedge plot for eSFR ISO, including recommended metric.

Light Source

The most uniform light source available would be an integrating sphere, but these come with considerable size and expense. After considering how the light source uniformity impacts their results, most lab & manufacturing tests use LED or fluorescent lightboxes with flat-panel diffusers. Some customers choose a larger lightbox because that leads to greater uniformity within the central image plane area. We have performed a study of lightbox uniformity to see how different models compare. 

To perform tests with a transmissive chart setup, devices with built-in light sources will need to have that light source disabled. (more…)