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.) […]

Since SFRplus (and eventually eSFR ISO, which uses almost all the same settings) is included in IT EXE and DLL, users may sometimes need to examine or edit the INI file used to control IT versions. Most of the settings in the [sfrplus] or [esfriso] section are set by one of the three SFRplus or eSFR ISO Settings windows that can be opened when SFRplus is run in Rescharts (or by clicking SFRplus setup in the Imatest main window). A few are set by responses to other windows or user actions. Settings that affect only Rescharts mode (and hence do […]

Imatest SFR allows you to analyze and display several regions of interest (ROIs) in an image. Display options can be selected from three dropdown windows from the SFR settings window. Multi-ROI plots lets you choose the plot type: 1D or 2D; units in Cycles/Pxl, LW/PH (Line Widths per Picture Height), or LP/PH (Line Pairs per Picture Height).The 1D summary plots, which display results as a function of the distance from the image center, may be difficult to read for lenses that are poorly centered and hence have asymmetrical response. In most cases 2D summary plots are far more readable. 1D […]

* indicates that this field will be described in more detail at the bottom of this document (Much of the text at the bottom will be common to several ini file reference pages). 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 […]

Imatest Rescharts slanted-edge modules perform highly automated measurements of several key image quality factors using specially-designed test charts. The user never has to manually select Regions of Interest (ROIs). This page covers results that are (mostly) not derived from the slanted-edges themselves, including Noise (best in eSFR ISO) Distortion  (differing detail in different modules; best with SFRplus and eSFR ISO. Described in detail here. Tonal response*  (no noise statistics for SFRplus) Color accuracy*  when used with an SFRplus, eSFR ISO, or SFRreg center charts that contain a color pattern Vanishing resolution, aliasing, and Moiré from Wedge patterns in eSFR ISO ISO sensitivity*  (Saturation-based and […]

Imatest Rescharts slanted-edge modules perform highly automated measurements of several key image quality factors using specially-designed test charts. The user does not need to manually select Regions of Interest (ROIs). This page covers results that are derived from the slanted-edges (i.e., not from grayscale, color, or wedge patterns). It also covers text output (CSV and JSON) files. Sharpness, expressed as Spatial Frequency Response (SFR), also known as the Modulation Transfer Function (MTF), can be displayed in several ways for individual edges or from the entire pattern, Lateral Chromatic Aberration Information capacity Other results, not derived from slanted-edges are covered in Part […]

Introduction – Using raw files – Bayer raw and RCCC files – LibRaw demosaicing (for commercial raw files)  Differences with in-camera JPEGs – Monochrome images – Bayer frequency units  DNG files – Rawview utility – Generalized Read Raw (for binary raw files)  Decompanding – Estimating image width & height – Creating Synthetic raw images    The unprocessed digital output of an image sensor is called RAW image data. In this document, we sometimes refer to raw files from commercial cameras or development systems as Camera raw to distinguish them from Bayer raw files, which are standard monochrome image files that contain undemosaiced […]

Automatic region detection in SFRplus and eSFR ISO tolerates moderate amounts of optical distortion (pincushion or barrel), but it has definite limits. In this page we describe special versions of SFRplus and eSFR ISO charts that can work (i.e., can be detected automatically) with highly barrel-distorted (“fisheye“) lenses, with fields of view up to around 160 degrees— which are used in a number of applications, particularly for automotive rear-view and sports cameras. Cameras with fields of view over 160 degrees— even approaching 360 degrees— can be tested with the SFRreg module, which uses multiple individual “registration mark” charts facing the […]

Although sharpness is an important image quality factor, a sharper lens is not always better. A lens can be too sharp for a sensor, resulting in disturbing visual artifacts. These artifacts, which include “stair-stepping” and moiré patterns (low frequency patterns that can be strongly colored), can appear because digital cameras— and all digitally sampled systems— have a maximum spatial frequency, called the Nyquist frequency, beyond which scene information cannot be correctly reproduced. Any information above the Nyquist frequency that reaches the sensor will be “aliased” to a lower spatial frequency, which can result in the artifacts described below. Sampling – Nyquist […]