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        <title>en:yanding:image_quality_evaluation:image_quality_factors:mtf_sfr_analysis_and_testing</title>
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        <description>MTF (Modulation Transfer Function)

I.Definition

MTF (Modulation Transfer Function) is the modulus of the Optical Transfer Function (OTF), defined as the ratio of the output modulation of the system to the input modulation, describing the contrast transfer capability of an imaging system at different spatial frequencies.$$MTF(f)=\frac{M_{\text{out}}(f)}{M_{\text{in}}(f)}=|OTF(f)|$$$M$$$M=\frac{I_{\max}-I_{\min}}{I_{\max}+I_{\min}}$$$I_{max}$$I_{min}$</description>
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        <dc:date>2026-07-10T08:03:33+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:ieee_2020_2024_flicker</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:ieee_2020_2024_flicker&amp;rev=1783670613&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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IEEE 2020-2024 Flicker Test

1. Definition of Flicker

Flicker refers to the phenomenon of periodic brightness fluctuations, banding, or local brightness instability in images captured by a camera. This phenomenon is essentially caused by a mismatch in temporal sampling. LED lights typically emit light in pulses at frequencies of hundreds of times per…</description>
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        <dc:date>2026-07-24T02:37:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:lidar:fmcw</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:lidar:fmcw&amp;rev=1784860639&amp;do=diff</link>
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Frequency Modulated Continuous Wave (FMCW)

1. Definition and Principles:

Frequency Modulated Continuous Wave (FMCW)$\Delta t$$\Delta t/2$$c$$3 \times 10^8 \, \text{m/s}$$$r = \frac{\Delta t}{2} \times c$$$f_d$$\lambda$$$v = \frac{f_d \times \lambda}{2}$$</description>
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        <dc:date>2026-08-14T09:33:39+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:image_quality_factors:sharpness</title>
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        <description>Acutance

I. Definition

Acutance is an objective physical quantity used to measure image clarity. By contrast, sharpness is the subjective human perception of image clarity; the two are distinct concepts.

Early acutance calculations were based on the gradient of an edge profile: the steeper the transition, the higher the value. However, an edge gradient describes only the physical rate of transition and does not account for the fact that images are ultimately perceived by the human visual syst…</description>
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        <dc:date>2026-08-20T02:50:53+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:image_quality_factors:noise</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:image_quality_factors:noise&amp;rev=1787194253&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Noise

I. Definition

Image noise refers to the unintended interference superimposed on the target signal during image acquisition, transmission, or processing. Its external manifestation is the $\sigma_{\text{signal}} = \sqrt{N_{\text{signal}}}$$I_{\text{dark}} \propto A \cdot T^3 e^{-\frac{E_g}{kT}}$$I_{\text{dark}}$$T$$E_g$$k$$A$$\sigma_{\text{dark…</description>
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        <dc:date>2026-07-23T11:59:46+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:sfr</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:camera_test_cases:sfr&amp;rev=1784807986&amp;do=diff</link>
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Spatial Frequency Response (SFR)

1. Concept of Spatial Frequency Response

Spatial Frequency Response (</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-07-10T08:03:02+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:tools:riqa_software:riqa_camera_resolution_module</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:tools:riqa_software:riqa_camera_resolution_module&amp;rev=1783670582&amp;do=diff</link>
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RIQA-Camera Resolution Module

Resolution is used to evaluate the ability of an imaging system (such as cameras, lenses, etc.) to reproduce details at different spatial frequencies. This module supports the analysis of various mainstream test targets, including slanted-edge targets, line pair targets, Siemens star targets, and dead leaves targets, mee…</description>
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        <dc:date>2026-07-24T02:37:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:lidar:lidar_overview</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:lidar:lidar_overview&amp;rev=1784860639&amp;do=diff</link>
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LiDAR

1. What is LiDAR?

LiDAR (Light Detection and Ranging) is an active sensing technology that acquires precise dimensions and spatial configurations of targets by emitting laser beams and analyzing the echo signals (e.g., Time of Flight (ToF) or frequency difference (FMCW)). Compared to passive imaging solutions that rely on ambient light (such a…</description>
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        <dc:date>2026-07-24T05:20:27+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:radiation_and_luminescence:light</title>
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Light

Light, as a core carrier spanning the fields of optical engineering and electronic information, is a key medium for energy transfer and information transmission. From basic illumination and high-precision imaging to fiber-optic communication, laser precision manufacturing, and cutting-edge quantum technologies, the applications of light are dee…</description>
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        <dc:date>2026-07-10T08:03:31+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:gb_t_43249_2023_passive_ir</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:gb_t_43249_2023_passive_ir&amp;rev=1783670611&amp;do=diff</link>
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GB/T 43249-2023 &quot;Passive Infrared Detection Systems for Automobiles&quot;

GB/T 43249-2023 “Passive Infrared Detection Systems for Automobiles$\Delta T=2\text{K}$$n$$N$$n$$S$$$\text{NETD} = \frac{\Delta T}{S/N} $$$\Delta T$$S$$N$$$MRTD = \frac{|\Delta T_1| + |\Delta T_2|}{2}$$</description>
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        <dc:date>2026-07-10T08:03:14+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:adas_test_cases:flicker</title>
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        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Flicker

1. What is Flicker


In the field of automotive imaging, Flicker refers to the phenomenon of periodic brightness fluctuations, banding, or local brightness instability in images captured by a camera. This phenomenon is not the</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:geometric_optics:basic_properties_of_light&amp;rev=1784627396&amp;do=diff">
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        <dc:date>2026-07-21T09:49:56+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:geometric_optics:basic_properties_of_light</title>
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        <description>Basic Properties of Light

1. Overview

Light is electromagnetic radiation exhibiting wave-particle duality, serving as a fundamental carrier for energy transfer and information transmission in modern technology.


Its behavior is described by three core models:$\theta_i = \theta_r$$n_1$$n_2$$$n_1 \sin\theta_1 = n_2 \sin\theta_2$$$\theta_1$$\theta_2$$$c = \lambda \nu$$$c$$\lambda$$ \nu$$c$$$E = h\nu = \frac{hc}{\lambda}$$$h$$\nu$$c$$\lambda$</description>
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        <dc:date>2026-07-23T12:51:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_sharpness</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_sharpness&amp;rev=1784811079&amp;do=diff</link>
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CMS Sharpness

Why Measure Sharpness in CMS?


As an electronic replacement for traditional optical rearview mirrors, the $$\text{MTF}50_{\langle 1:1 \rangle} \geq \frac{1}{2}\text{MTF}10_{\text{MIN}\langle 1:1 \rangle} \left[ \frac{\text{LW}}{\text{PH}} \right]$$$$\text{MTF}50_{\langle 1:1 \rangle} \geq \frac{1}{2} \times \left( \frac{1}{2} \text{MTF…</description>
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        <dc:date>2026-07-24T03:00:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:image_quality_factors:spatial_frequency_units</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:image_quality_factors:spatial_frequency_units&amp;rev=1784862019&amp;do=diff</link>
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Spatial Frequency Units

Units and Applications of Spatial Frequency



Conversion Formulas

Different units can be converted using parameters such as image height and focal length. The conversion formulas are as follows:$\frac{MTF(C/P)}{\text{pixel pitch}}$$2 \times MTF\left(\frac{LP}{PH}\right)$$2 \times MTF\left(\frac{C}{P}\right) \times PH$$MTF\le…</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:iso_12233_sfr</title>
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ISO 12233: SFR Testing

Overview


The ISO 12233 standard specifies methods for measuring the resolution and spatial frequency response (SFR)</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:iso_16505_cms_depth_of_field&amp;rev=1783670615&amp;do=diff">
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:iso_16505_cms_depth_of_field</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:iso_16505_cms_depth_of_field&amp;rev=1783670615&amp;do=diff</link>
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ISO 16505: CMS Depth of Field Test

Definition:

Depth of field is the distance range over which the imaging resolution of the $$MTF10_{(1:1)} \geq 0,9^*MTF10_{MIN(1:1)} \left[ \text{LW/PH} \right]\tag{1}$$$$MTF10_{(1:1)} \geq \frac{1}{2} MTF10_{MIN(1:1)} \left[ \text{LW/PH} \right]]\tag{2}$$$$MTF10_{\text{MIN}(1:1)/\text{hor}} = \left( \frac{W_{\text…</description>
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        <dc:date>2026-08-11T02:56:43+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_depth_of_field</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_depth_of_field&amp;rev=1786417003&amp;do=diff</link>
        <description>CMS Depth of Field

I.Definition

Depth of Field (DoF) of a CMS (Camera–Monitor System) refers to the object-distance range behind the vehicle over which targets can be sharply imaged.


In optical imaging, object points outside the focal plane produce defocused blur on the image sensor, typically described by the \(MTF10_{(1:1)}\)$$MTF10_{(1:1)} \geq 0.9^*MTF10_{MIN(1:1)} \left[ \text{LW/PH} \right]\tag{1}$$$$MTF10_{(1:1)} \geq \frac{1}{2} MTF10_{MIN(1:1)} \left[ \text{LW/PH} \right]]\tag{2}$$$…</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:tools:collimators:focal_length_matching&amp;rev=1783670589&amp;do=diff">
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        <dc:date>2026-07-10T08:03:09+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:tools:collimators:focal_length_matching</title>
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Focal Length Matching Between Collimator and DUT

When testing a DUT using a collimator, the collimating objective Lcol of the collimator and the imaging objective Ldut of the DUT form an optical imaging system. The image of the target formed by Lcol serves as the object for Ldut. Focal length is one of the primary parameters of Lcol. In collimator se…</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-07-10T08:03:06+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:tools:light_sources:traffic_light_simulation_platform</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:tools:light_sources:traffic_light_simulation_platform&amp;rev=1783670586&amp;do=diff</link>
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Yanding Road Traffic Signal Light Simulation and Testing Platform

With the continuous development of autonomous driving technology, corresponding testing methods must also be upgraded synchronously. Current testing mostly focuses on lane detection, object tracking, and scene understanding. However, road traffic signal light recognition, as a critical…</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:radiometry_photometry:radiant_energy&amp;rev=1783670573&amp;do=diff">
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        <dc:date>2026-07-10T08:02:53+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:radiometry_photometry:radiant_energy</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:radiometry_photometry:radiant_energy&amp;rev=1783670573&amp;do=diff</link>
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Radiant Energy

I. Definition

Radiant Energy is the energy carried by electromagnetic radiation during its emission, propagation, or absorption. It is a fundamental energy quantity in radiometry, used to characterize the total energy transferred by radiation, and is denoted by the symbol: $Q_e$$$Q_e = \int_{t_1}^{t_2} \Phi_e(t) dt$$$\Phi_e(t)$$t_1-t_…</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:image_quality_factors&amp;rev=1787323226&amp;do=diff">
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        <dc:date>2026-08-21T14:40:26+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:image_quality_factors</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:image_quality_factors&amp;rev=1787323226&amp;do=diff</link>
        <description>Image Quality Factors

This section covers common image quality issues in imaging systems, including:

	*  MTF (Modulation Transfer Function)
	*  Acutance
	*  Distortion
	*  Flare
	*  White Balance
	*  Noise
	*  Dynamic Range
	*  Chromatic Aberration
	*  Field of View
	*  Uniformity (Shading)
	*  Spatial Frequency Units</description>
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        <dc:date>2025-11-07T09:02:46+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像质量评价:标准化测试:ieee_2020-2024_flicker测试</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E8%AF%84%E4%BB%B7:%E6%A0%87%E5%87%86%E5%8C%96%E6%B5%8B%E8%AF%95:ieee_2020-2024_flicker%E6%B5%8B%E8%AF%95&amp;rev=1762506166&amp;do=diff</link>
        <description>IEEE 2020-2024 Flicker测试

一、闪烁（Flicker)的定义

闪烁（Flicker）指相机拍摄的图像中出现周期性明暗波动、条纹或局部亮度不稳定的现象。该现象本质上是时间采样不匹配导致的问题，LED 灯通常以每秒数百次的频率脉冲发光，其表观亮度通过调整脉冲的占空比（即亮灯时间在一个周期内的占比）来控制，而由于人眼相当于一个天然的时间低通滤波器，这种高频脉冲在视觉上会被 “平滑” 为持续稳定的光效，因此人眼看到的 LED 灯处于恒定亮灯状态。但拍摄光源的相机可能会与这些波动以相同的时间尺度进行曝光，使得相机更容易捕捉到光源本身的动态变化。$$ FMI = 100 \times \frac{x_{\max} - x_{\min}}{x_{\max} + x_{\min}} $$$x_{\max}$$x_{\min}$$$ FDI = Prob\left(\frac{x_{\mathrm{meas}} - x_{\mathrm{ref\,off}}}{x_{\mathrm{ref\,off}}} \geq \tau \right)$$$FDI$$Prob$$x_{\m…</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:qc_t_1128_2019&amp;rev=1783670617&amp;do=diff">
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:qc_t_1128_2019</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:standardized_testing:qc_t_1128_2019&amp;rev=1783670617&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Image Solutions for &quot;QC/T 1128-2019: Automotive Cameras&quot;

Overview

“QC/T 1128-2019: Automotive Cameras$\text{SNR (dB)} = 20\log_{10}\left(\frac{\text{Si}}{\text{Ni}}\right)$${Si}$\( i \)${Ni}$\( i \)$$\text{DR} = 20 \left( D_{\text{SNR}=1} - D_{\text{SNR}=\text{MAX}} \right)$$$D_{\text{SNR}=1}$$D_{\text{SNR}=\text{MAX}}$$t_{on}$$t_{SL}$$$\theta_{\tex…</description>
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        <dc:date>2026-07-23T11:59:46+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:frame_rate</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:camera_test_cases:frame_rate&amp;rev=1784807986&amp;do=diff</link>
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Frame Rate

1. What is Frame Rate?

Essentially, a video is composed of a sequence of still images. These still images are the smallest unit of a video, known as frames. Frame rate refers to the number of consecutive frames captured or displayed per second, measured in Hz (Hertz) or frames per second (fps). For example, 30 fps means 30 consecutive fra…</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:mtf_sfr_dead_leaves</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:camera_test_cases:mtf_sfr_dead_leaves&amp;rev=1783670595&amp;do=diff</link>
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MTF/SFR Measurement — Dead Leaves Method

Principle:

Based on a random circular texture pattern that closely resembles natural scenes, this method extracts the texture Power Spectral Density (PSD) and subtracts the noise. It then calculates the ratio of the modulation amplitude at each frequency to the target modulation to obtain the MTF/SFR values. …</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:mtf_sfr_siemens_star</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:camera_test_cases:mtf_sfr_siemens_star&amp;rev=1783670595&amp;do=diff</link>
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MTF/SFR Measurement — Siemens Star Method

Principle:

Based on the radial frequency gradient characteristics of radial sinusoidal wedge patterns, this method directly obtains the modulation MTF values at different spatial frequencies through pixel reading, sinusoidal curve fitting, and modulation calculation (without the need for Fourier transform). …</description>
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        <dc:date>2026-07-10T08:03:06+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:tools:light_sources:matrix_traffic_light</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:tools:light_sources:matrix_traffic_light&amp;rev=1783670586&amp;do=diff</link>
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Yanding Matrix Traffic Light Helps ADAS Systems Accurately Recognize Traffic Light Status

Introduction</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:image_sensors:bayer_filter&amp;rev=1784862274&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2026-07-24T03:04:34+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:image_sensors:bayer_filter</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:image_sensors:bayer_filter&amp;rev=1784862274&amp;do=diff</link>
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Bayer Filter

1. Why is a Bayer Filter Needed?

The core of an image sensor is a silicon-based photodiode, which can only measure the amount of charge generated by incident light and cannot directly perceive the color of the light.</description>
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        <dc:date>2026-07-24T02:37:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:lidar:angular_resolution</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:lidar:angular_resolution&amp;rev=1784860639&amp;do=diff</link>
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Angular Resolution

1. What is Angular Resolution?

Angular resolution refers to the angle formed by the central axes of two adjacent laser detection points at the ranging center during the scanning and detection process of a LiDAR. Depending on the scanning direction, it can be divided into $\Delta L$$\theta$$$\Delta L = d \cdot \tan(\theta) \approx …</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-07-24T02:37:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:lidar:ranging_capability</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:lidar:ranging_capability&amp;rev=1784860639&amp;do=diff</link>
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Ranging Capability

I. Introduction

Ranging capability is a key fundamental metric for evaluating the detection performance of $P_t$$A_r$$\alpha$$R$$\sqrt{\rho}$$R \propto \sqrt{\rho}$$$P_r = P_t \cdot \frac{A_r}{R^2} \cdot \rho \cdot \eta_{sys} \cdot \exp(-2\alpha R)$$$P_r$$P_t$$A_r$$R$$\rho$$\eta_{sys}$$\alpha$</description>
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        <dc:date>2026-07-24T02:37:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:imaging_systems:lidar:tof</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:imaging_systems:lidar:tof&amp;rev=1784860639&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Time of Flight (ToF)

Time of Flight (ToF) is a sensing technology that acquires the depth or distance of a target object by measuring the time required for light, sound, or particles to travel a certain distance through a medium.$\Delta t$$ c $$$d = \frac{c \cdot \Delta t}{2}$$</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:colorimetry:metamerism</title>
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        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Is Metamerism Far Removed from Our Daily Lives?

Metamerism is a colorimetric term used to describe the phenomenon where color stimuli with different spectral compositions produce the same color perception (i.e., have the same tristimulus values). The English word for this is</description>
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        <title>en:yanding:imaging_basics:optics:geometric_optics:entrance_pupil</title>
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        <description>Entrance Pupil

When observing the human eye, a dark circular opening known as the pupil can be seen, through which incident light enters the eye. Physiologically, the pupil is the aperture located at the center of the iris. However, the visible pupil is not the physical opening itself, but the image of the pupil formed by the refractive structures in front of it, such as the cornea and aqueous humor.</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:radiation_and_luminescence:blackbody</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:radiation_and_luminescence:blackbody&amp;rev=1784870427&amp;do=diff</link>
        <description>Blackbody

I. What is a Blackbody?

A blackbody is an idealized physical model under thermal equilibrium (energy conservation), which completely absorbs all wavelengths of incident electromagnetic radiation without reflection or transmission.


Per the law of conservation of energy:$$M_\lambda(\lambda, T) = \frac{c_1}{\lambda^5} \frac{1}{e^{\frac{c_2}{\lambda T}} - 1}$$$M_\lambda$$W \cdot m^{-3}$$\lambda$$T$$c_1 = 2\pi h c^2$$W \cdot m^2$$c_2 = \frac{hc}{k_B}$$m \cdot K$$k_B $$J \cdot K^{-1}$$\l…</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:radiometry_photometry:luminous_intensity</title>
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        <description>Luminous Intensity

Definition

Luminous intensity (symbol:$I_v$ ) describes the intensity of a light source in a given direction, defined as the luminous flux emitted per unit solid angle. It is an inherent property of the light source, independent of the source area and observation distance.$$ I_v = \frac{\mathrm{d}\Phi_v}{\mathrm{d}\Omega} $$$I_v$$\Phi_v$$\Omega$\(\mathrm{cd}\)\(540\times 10^{12}\ \mathrm{Hz}\)\(K_{\mathrm{cd}}\)\[
K_{\mathrm{cd}} = 683\ \mathrm{lm\,W^{-1}}.
\]\(\Phi_v\)\(I_v…</description>
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        <dc:date>2026-07-15T12:13:13+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:keywords</title>
        <link>https://wiki.yanding.com/doku.php?id=en:keywords&amp;rev=1784117593&amp;do=diff</link>
        <description>dynamic range/color reproduction/spatial frequency response/uniformity/distortion/flare/flicker/CMS/test charts</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:test_cases</title>
        <link>https://wiki.yanding.com/doku.php?id=en:test_cases&amp;rev=1784879388&amp;do=diff</link>
        <description>Test Cases

This section provides practical test cases for image quality evaluation, organized by application:

	*  Camera Test Cases
		*  Image Quality Evaluation Overview
		*  Dynamic Range
		*  Noise
		*  Sharpness
		*  White Balance
		*  Distortion
		*  Uniformity
		*  Color Reproduction
		*  Chromatic Aberration
		*  Field of View
		*  Exposure Time
		*  Frame Rate
		*  Glare
		*  Spatial Frequency Response (SFR)
		*  Texture Loss
		*  Gray Scale Response
		*  Image Stabilization
		*  MTF/S…</description>
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        <dc:date>2026-08-21T14:40:26+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>wiki:langswitch_map</title>
        <link>https://wiki.yanding.com/doku.php?id=wiki:langswitch_map&amp;rev=1787323226&amp;do=diff</link>
        <description>﻿

Language Switch Map

维护说明：

	*  第一列是中文页面ID
	*  第二列是英文页面ID
	*  只改表格，不要改格式
	*  新增映射时一行一条
 中文页ID  英文页ID  yanding:成像基础知识:光学:几何光学:主光线角</description>
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        <dc:date>2026-08-20T02:50:53+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像质量评价:图像质量指标:mtf_调制传递函数</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E8%AF%84%E4%BB%B7:%E5%9B%BE%E5%83%8F%E8%B4%A8%E9%87%8F%E6%8C%87%E6%A0%87:mtf_%E8%B0%83%E5%88%B6%E4%BC%A0%E9%80%92%E5%87%BD%E6%95%B0&amp;rev=1787194253&amp;do=diff</link>
        <description>MTF（调制传递函数）

一、定义

MTF（调制传递函数，Modulation Transfer Function）是光学传递函数（OTF）的模，定义为系统输出调制度与输入调制度之比，描述成像系统在不同空间频率下对比度传递能力。$$MTF(f)=\frac{M_{\text{out}}(f)}{M_{\text{in}}(f)}=|OTF(f)|$$$M$$$M=\frac{I_{\max}-I_{\min}}{I_{\max}+I_{\min}}$$$I_{\max}$$I_{\min}$$MTF_{10}$$ f_{N}= 1 / (2 x PixelPitch)$</description>
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        <dc:date>2025-10-31T07:23:05+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像质量评价:标准化测试:iso_12233_sfr测试</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E8%AF%84%E4%BB%B7:%E6%A0%87%E5%87%86%E5%8C%96%E6%B5%8B%E8%AF%95:iso_12233_sfr%E6%B5%8B%E8%AF%95&amp;rev=1761895385&amp;do=diff</link>
        <description>ISO 12233：SFR测试

概述


ISO 12233标准规定了测量数字相机的分辨率和空间频率响应 （SFR） 的方法。该标准首次发布于 2000 年，目前最新的是 2024 年发布的第 5 版。

使用标准：

ISO 12233    Photography— Electronic still picture imaging — Resolution and spatial frequency responses

技术委员会：</description>
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        <dc:date>2026-07-10T08:03:30+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:standardized_testing:emva_1288</title>
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        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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EMVA 1288: Standard for Characterization of Image Sensors and Cameras

1. Background

The EMVA 1288 standard$\eta$$K$$K = \frac{\text{DN}}{\text{e}^-}$$\mathrm{SNR_{p,max}}$$T_d$$$ \eta = \frac{\mu_e}{\mu_p} \tag{1}$$$\mu_p$$\mu_e$$$\mu_y = \mu_{y,\text{dark}} + K \eta \mu_p \tag{2}$$$\mu_y$$\mu_{y,\text{dark}}$$K$$\text{DN}/e^-$$$\eta = \frac{\mu_y -…</description>
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        <dc:date>2026-07-23T12:54:34+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像基础知识:成像系统:激光雷达:激光雷达</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E5%9F%BA%E7%A1%80%E7%9F%A5%E8%AF%86:%E6%88%90%E5%83%8F%E7%B3%BB%E7%BB%9F:%E6%BF%80%E5%85%89%E9%9B%B7%E8%BE%BE:%E6%BF%80%E5%85%89%E9%9B%B7%E8%BE%BE&amp;rev=1784811274&amp;do=diff</link>
        <description>激光雷达

一、什么是激光雷达？

激光雷达（LiDAR）是一种通过发射激光束并解析回波信号（如飞行时间 ToF 或频率差 FMCW等）来获取目标精确维度及空间构型的主动传感技术。相比依赖环境光的被动成像方案（如摄像头），激光雷达具备较强的抗光照干扰能力，在极暗或强逆光条件下仍能稳定输出厘米级精度的三维点云数据，是实现物理环境数字化重构的关键手段。\(\Delta t\)$d = \frac{c \cdot \Delta t}{2}$$(x, y, z)$…</description>
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        <dc:date>2026-07-23T12:54:34+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像基础知识:成像系统:激光雷达:调频连续波fmcw</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E5%9F%BA%E7%A1%80%E7%9F%A5%E8%AF%86:%E6%88%90%E5%83%8F%E7%B3%BB%E7%BB%9F:%E6%BF%80%E5%85%89%E9%9B%B7%E8%BE%BE:%E8%B0%83%E9%A2%91%E8%BF%9E%E7%BB%AD%E6%B3%A2fmcw&amp;rev=1784811274&amp;do=diff</link>
        <description>调频连续波FMCW

一. 定义与原理：

调频连续波FMCW (Frequency Modulated Continuous Wave) 是一种基于相干检测技术的高阶感知方案。不同于传统 ToF（飞行时间法）通过脉冲“打表计时”，FMCW 发射的是频率随时间受控变化的连续激光束。它利用波的干涉原理，测量回波与当前发射信号之间的$\Delta t$$\Delta t/2$$c$$3 \times 10^8 \, \text{m/s}$$$r = \frac{\Delta t}{2} \times c$$$f_d$$\lambda$$$v = \frac{f_d \times \lambda}{2}$$…</description>
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        <dc:date>2026-08-12T07:46:24+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像质量评价:测试用例:camera测试用例:空间频率响应_sfr</title>
        <link>https://wiki.yanding.com/doku.php?id=yanding:%E6%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E8%AF%84%E4%BB%B7:%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B:camera%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B:%E7%A9%BA%E9%97%B4%E9%A2%91%E7%8E%87%E5%93%8D%E5%BA%94_sfr&amp;rev=1786520784&amp;do=diff</link>
        <description>空间频率响应（SFR）

一、空间频率响应的概念

空间频率响应（Spatial Frequency Response，SFR）指的是正弦输入的振幅（即对比度）随空间频率变化的衰减程度，可将人眼主观感知的“清晰度”转化为可测量的物理参量，用于评估​​成像系统（如相机、镜头等）对不同空间频率细节的再现能力​​。</description>
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        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:image_quality_evaluation</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:camera_test_cases:image_quality_evaluation&amp;rev=1784807986&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Image Quality Assessment

Overview

Image Quality Assessment (IQA) refers to the subjective and objective analysis and evaluation of the imaging performance (such as resolution, noise, distortion, color, dynamic range, etc.) of an imaging system under given conditions (such as the captured scene, lighting environment, and display device input of a cam…</description>
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        <dc:date>2026-07-23T11:59:46+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:camera_test_cases:texture_loss</title>
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        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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Texture Loss

1. Concept of Texture


In the field of digital imaging, texture generally refers to low-contrast details. For example, the leaves on a tree or each blade of grass in a prairie are details, also known as texture. In principle, a camera should be able to reproduce these details. For a camera, distinguishing texture from unwanted noise in …</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-07-10T08:03:29+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_frame_rate</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:test_cases:cms_test_cases:cms_frame_rate&amp;rev=1783670609&amp;do=diff</link>
        <description>FIXME This page is not fully translated, yet. Please help completing the translation.

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I. Definition

CMS frame rate refers to the total number of valid images completely displayed by the vehicle Camera Monitor System (CMS) per unit of time, encompassing image capture, processing, transmission, and display. The unit is</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:image_quality_evaluation:tools:collimators:pupil_matching&amp;rev=1786069320&amp;do=diff">
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        <dc:date>2026-08-07T02:22:00+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:image_quality_evaluation:tools:collimators:pupil_matching</title>
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        <description>Collimator–DUT Pupil Matching

The exit pupil (ExP) is the image of the aperture stop formed by the optical elements that lie between the stop and the image plane. It serves as the common opening through which all rays leave the optical system, and its centre is located at the intersection of the chief rays in image space.</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:radiometry_photometry:luminous_efficacy&amp;rev=1783670570&amp;do=diff">
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        <dc:date>2026-07-10T08:02:50+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>en:yanding:imaging_basics:optics:radiometry_photometry:luminous_efficacy</title>
        <link>https://wiki.yanding.com/doku.php?id=en:yanding:imaging_basics:optics:radiometry_photometry:luminous_efficacy&amp;rev=1783670570&amp;do=diff</link>
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Luminous Efficacy

1. Definition

Luminous efficacy is a metric that measures the efficiency of a light source in converting energy into visible light. It is defined as the ratio of luminous flux ($\Phi_V$${lm·W}^{-1}$$K(\lambda)$$$K = \frac{\Phi_V}{\Phi_e} = \frac{\int_0^\infty K(\lambda)\Phi_{e,\lambda}\mathrm{d}\lambda}{\int_0^\infty \Phi_{e,\lambd…</description>
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