This page is a reference for the INI files used to store Imatest settings, particularly imatest-v2.ini, which is the basis of ini files used to control Imatest IT. It focuses on INI file settings that are used by several modules and are of interest to users of Imatest IT and the Functional Interface.  INI file structure – Extracting an INI file for IT – Running from a Custom File – INI File Monitor – [api] (for Imatest IT) [LibRaw] – [rdraw] (Generalized Read Raw) – Secondary Readouts – Miscellaneous To keep this document to a reasonable length, the INI references for Imatest IT modules are stored […]

Introduction This page briefly illustrates how to use the Imatest with Omnivision OVTAPantherM. Please note that Omnivision cameras are not supported in the macOS and Linux version of Imatest. However, Imatest supports other development systems to varying degrees. Contact us for details. Load images directly from Omnivision sensors. This eliminates the need to capture images separately, store them, then load them individually into Imatest, dramatically improving productivity. Download and Install Software To download Imatest software, go to store.imatest.com/software.html Download and open the Imatest Master self-extracting executable. This will install the Imatest Master edition and the Matlab Compiler Runtime (MCR), which is […]

Introduced in Imatest 4.2, the Imatest Educational Apps serve to demonstrate mathematical concepts that directly relate to the understanding of image quality factors. The Imatest Educational Apps demonstrate Nyquist sampling theorem, the decomposition of an image’s Fourier transform, the Modulation Transfer Function of a slanted edge, chromatic aberration and signal to noise ratio (SNR). As an educational resource, this utility is available through the main window of your Imatest software. To access the Imatest Educational Apps, go to the Imatest main window and select Help, then Educational Apps…. A Welcome splash screen will open by default. Select the tabs across […]

Starting with Imatest 3.9, Imatest provides strong support for CPIQ (Camera Phone Image Quality)* Phase 2 measurements. Further detail is available in the CPIQ 2.0 Specifications & Test Methods document. Contact us if you need further information. We are members of CPIQ, and we will will add updated measurements as they become available (expected in early 2016). *CPIQ formerly belonged to I3A (International Imaging Industry Association). It now belongs to the IEEE Standards Association, Working Group P1858. SFR and Acutance For CPIQ, sharpness is measured as Spatial frequency response (SFR) (also called Modulation Transfer Function (MTF)). The SFR, SFRplus ( […]

News:  Imatest 2021.2  1D Fourier spectrum plots have been added to Cross-sections. QR or bar codes can be read in the Rectangle analysis.   Image Statistics is an interactive utility that lets you examine a number of image properties, including Vertical and horizontal cross-sections with adjustable thickness. Using a larger thickness mitigates the effects of noise. Pixel levels or 1D Fourier spectra can be plotted. Properties of rectangular or square (eyedropper) regions, including rectangle position, Mean values of R,G,B, and Y (luminance) channels, Log10(mean/max), Noise (sigma), Noise corrected for nonuniformity, SNR (Signal/Noise), SNR dB, and Mean L*a*b* (when color space has […]

Introduction The Imatest Image Stabilization/Sharpness Compare module is a postprocessor for SFRplus that Measures the effectiveness of Optical Image Stabilization (abbreviated as IS or OIS) by comparing the sharpness (MTF or related lengths) of selected near-horizontal and near-vertical edges from three similar SFRplus images: Unshaken. Shaken without Image Stabilization. (Some recent cameras lack the ability to turn IS off. There are several approaches to measuring IS effectiveness in this case. One is to have a very precise vibratory apparatus with known vibration angles. Expen$ive. Another is to substitute a camera with similar pixel configuration and lens focal length, but no […]

Overview Why Imatest?     |     Test Charts     |     Lighting     |     Image Capture Technique     |     Setting up Your Lab     |     Using Imatest Software If you are getting started with Imatest — or need a good reference on using it — we recommend Imatest Instructions– Getting started. Why Imatest? Introduction Imatest charts and software allow you to measure the characteristics and quality of cameras and imaging systems. To begin measuring the resolution or color of your camera, you’ll need an image of a test chart. Imatest offers all-in-one test charts that can test […]

Operation – Image processing blocks – Displays and analysis – Remosaicing – Optical Character Recognition (OCR) Face and People Detection The Imatest Image Processing module, introduced in Imatest 4.4 and significantly enhanced in 4.5 and 5.0, simulates a number of image processing operations, including image degradations such as noise and blurring as well as image enhancements such as applying a Color Correction Matrix, tone mapping (used in High Dynamic Range (HDR) imaging), Unsharp Masking (USM), and bilateral filtering. You can instantly observe the visible effects of these operations by switching between unprocessed and processed images. You can see how processing affects several measurements, including […]

Overview and introduction to measurements   Summary table— Image quality factors and corresponding test charts and modules Sharpness Noise Tonal response & contrast Color accuracy Lens Distortion Light Falloff & Nonuniformities Blemishes Dynamic range  Lateral Chromatic Aberration Veiling Glare Color aliasing and moiré Exposure accuracy     ISO Sensitivity   Focus & defocus   Data compression losses Texture Detail Information capacity  Software artifacts  Overview and Imatest measurements  Image quality is one of those concepts that’s greater than the sum of its parts. But you can’t ignore the parts if your goal is to produce images of the highest quality. Every image […]

  This page describes details about the implementation of our CPIQ Solution.   For additional details about the initiative, see this presentation assembled by former committee chair Margaret Belska.   Imatest’s CPIQ Implementation Imatest 4.4+  supports IEEE CPIQ P1858TM (Camera Phone Image Quality) 2016 measurements. As members of CPIQ, we are strongly committed to providing convenient CPIQ-compliant and equivalent image quality measurements. NOTE: You should use at least Imatest 4.4.9 for the latest corrections to visual noise calculations. This page has similar order to chapters the CPIQ Standard, “P1858TM/D1 Standard for Camera Phone Image Quality“ document. The first four chapters […]

Introduction – Test chart – Photograph the chart – Framing – Lighting  Distance – Exposure – Run Imatest – Select files – Settings – Warnings – clipping  Batchview (combined results) – Checklist  Testing lenses: Introduction Lens quality (especially sharpness) has always been of major interest to photographers. Traditionally, lens testing has been highly tedious, best left to professionals and large publications. With Imatest, that has changed forever. All you need to do is photograph an SFRplus, eSFR ISO, or tilted Checkerboard chart (with careful technique of course), run the corresponding module (SFRplus, eSFR ISO, or Checkerboard), and interpret the results. The three […]

Spanish language translation: Glosario en Espanol Aliasing   Low frequency artifacts, sometimes quite disturbing, that appear when the image sensor receives significant signal energy above the Nyquist frequency. Color aliasing in Bayer sensors can be particularly troublesome. “Moire fringing” is a type of aliasing. See diagram in Nyquist frequency, below. Controlled by means of Anti-Aliasing (Optical Lowpass) Filters, which blur the image slightly (a classic tradeoff).  Aperture   The circular opening at the center of a lens that admits light. Generally specified by the f-stop (f-number), which is the focal length divided by the aperture diameter. A large aperture corresponds […]

Related web pages Using Color/Tone Interactive (Multicharts) – Interactive analysis of color & grayscale test charts Using Color/Tone Auto – Fixed (batch-capable) analysis of color & grayscale test charts Color/Tone / eSFR ISO Noise – including chroma, sensor (RAW), and visual noise Dynamic Range – a general introduction with links to Imatest modules that calculate it. Color Correction Matrix (CCM) Calculate a matrix (usually 3×3) for correcting image colors (often from RAW images)   Patch order In addition to linear step charts (which have a single row of patches), three Imatest modules— Stepchart, Color/Tone Interactive (formerly Multicharts), and Color/Tone Auto (formerly Multitest)— can analyze the tonal response and […]

Imatest Glosario Par Pablo Ruiz Garcia Aliasing. Elementos de baja frecuencia, a veces muy molestos, que aparecen cuando la energía de la señal alcanza al sensor digital por encima de la frecuencia Nyquist. El efecto de flecos moire son un tipo de alilasing. Aberración cromática. Es una característica de la lente que provoca que las distintas longitudes de onda formen foco en distintos puntos. Existen dos tipos; longitudinal, donde los diferentes colores forman su foco en planos distintos. Y, lateral, donde la longitud focal de la lente, por lo tanto la ampliación, es diferente para cada color. La aberración cromática […]

Gamma is the exponent of the equation that relates scene luminance with image pixel level. When the raw output of the image sensor, which is linear, is converted to image file pixels for a standard color space, the equation below is applied (very approximately, as we’ll explain below). pixel level = (RAW pixel level)gamma_camera ~= exposuregamma_camera      (1) When an image file is sent to a display (a monitor or print), Output luminance = (pixel level)gamma_display      (2) The total system gamma is gamma_camera * gamma_display.  Standard values of display gamma are 1.8 for older color spaces used in the Macintosh and 2.2 […]

Find the sharpest files in a batch Thanks for Andrea Nivini for suggesting this module. New in Imatest 5.2: A major redesign of Find Sharp Files. A summary plot is available. Results can be shown in an easy-to-read Table format. Results can be saved in CSV and JSON files.   Find Sharpest Files lets you quickly and conveniently rank the sharpness of a set of images. It works on any image— it doesn’t have to be a test chart. It runs much faster than any of the standardized sharpness measurements (slanted-edge, star, etc.). There are a number of situations where this capability […]

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.) […]

This page describes Imatest’s distortion calculations, comparing the different distortion formulas and modules. Distortion formulas – Modules – TV Distotion and Field of View – Image, Geometry, Distortion, FoV display Radial distortion plot – Distortion Contour plot – Compare results – Links Lens distortion has two basic forms, barrel and pincushion, as illustrated below. None Barrel Pincushion In addition to these three, there can be “mustache” or “wave” distortion, which is barrel near the center and pincushion near the edges, or vice-versa. Distortion formulas In the equations which apply to several modules, rd is the distorted (measured) radius normalized to the center-to-corner distance. […]

Lens aberrations, diffraction, and defocus (or focus error) are basic factors that limit lens sharpness. They are described in the following sections. Lens aberrations – Diffraction – Pixel response limits and Q – Visualizing Q – Defocus  Lens (Optical) Aberrations Imperfections in optical systems arise from a number of causes that include different bending of light at different wavelengths, the inability of spherical surfaces (or even ashperes) to provide clear images over large fields of view, changes in focus for light rays that don’t pass through the center of the lens, and many more (i.e., coma, stigmatism, spherical aberration, and […]

In January 2013 Imatest released the Spilled Coins test chart, which is an improved version of the Dead Leaves chart for measuring a camera’s fine texture response. (It’s available in the Imatest Store in both monochrome and color versions.) Shortly afterwards, Jason Cope of our partner company Image Quality Labs found an anomalous result and called me to find out what was wrong. When I looked at the image I realized that he’d done the test correctly. He had found an image whose processing defeated the intent of the dead leaves chart, which is to accurately measure a camera’s texture […]