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        <title>yanding:成像基础知识:成像系统:成像质量问题:mtf_sfr_深度解析与测试实践</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%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E9%97%AE%E9%A2%98:mtf_sfr_%E6%B7%B1%E5%BA%A6%E8%A7%A3%E6%9E%90%E4%B8%8E%E6%B5%8B%E8%AF%95%E5%AE%9E%E8%B7%B5&amp;rev=1772787268&amp;do=diff</link>
        <description>成像系统的“视力表”：MTF/SFR 深度解析与测试实践

当我们谈论成像系统的分辨率（客观物理极限），以及锐度与清晰度（主观视觉感知） 时，MTF/SFR 是量化这些主、客观维度的核心指标，它通过 MTF 曲线，直观地揭示了系统在不同细节尺度下的对比度传递能力。$M = \frac{I_{\max} - I_{\min}}{I_{\max} + I_{\min}}$$ f_{N}= 1 / (2 x PixelPitch)$$$Q = \frac{\sum_{i=1}^{N} SFR_i \, CSF_i}{\sum_{i=1}^{N} CSF_i}, \quad i = 1, 2, \dots, N \tag{L.2}$$\(SFR_i\)\(i\)\(CSF_i\)\(i\)\(N\)$$csf_{\text{lum}}(f) = \frac{(a \cdot f^c) e^{-bf}}{K} \tag{L.1}$$$a = 75$$b = 0.2$$c = 0.8$$K = 102.16$$f$$f_{cut}​ $$$f_{\text{cycles/degree}} = \f…</description>
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        <dc:date>2025-12-18T11:03:45+00:00</dc:date>
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        <title>yanding:成像质量评价:标准化测试:gb_t_43249-2023_汽车用被动红外探测系统</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:gb_t_43249-2023_%E6%B1%BD%E8%BD%A6%E7%94%A8%E8%A2%AB%E5%8A%A8%E7%BA%A2%E5%A4%96%E6%8E%A2%E6%B5%8B%E7%B3%BB%E7%BB%9F&amp;rev=1766055825&amp;do=diff</link>
        <description>GB/T 43249-2023《汽车用被动红外探测系统》

GB/T 43249-2023《汽车用被动红外探测系统》是中国首个针对车载被动红外探测技术的国家级技术标准，该标准全面规范了系统的技术要求、试验方法及检验规则，旨在提升车载红外探测设备在环境感知、夜视辅助、安全预警等场景下的可靠性与精准度。$\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:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像基础知识:成像系统:成像质量问题:锐度</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%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E9%97%AE%E9%A2%98:%E9%94%90%E5%BA%A6&amp;rev=1772782924&amp;do=diff</link>
        <description>锐度

一、锐度的本质

锐度是衡量图像细节表现力与边缘清晰度的核心指标。其本质在于不同色调或颜色区域交界处的对比度梯度——梯度越陡峭，边缘越鲜明，细节分离度就越强。它不仅决定了视觉上的“清晰感”，更是图像信息传递效率的体现。在评价体系中，它通常通过 Acutance与 MTF（调制传递函数）等指标进行量化分析。
$$Q = \frac{\sum_{i=1}^{N} SFR_i \, CSF_i}{\sum_{i=1}^{N} CSF_i}, \quad i = 1, 2, \dots, N \tag{L.2}$$\(SFR_i\)\(i\)\(CSF_i\)\(i\)\(N\)$$csf_{\text{lum}}(f) = \frac{(a \cdot f^c) e^{-bf}}{K} \tag{L.1}$$$a = 75$$b = 0.2$$c = 0.8$$K = 102.16$$f$$f_{cut}​ $$$f_{\text{cycles/degree}} = \frac{\pi D}{180 p} f_{\text{cycles/pixel}} = \frac{\pi D N…</description>
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        <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=1768528821&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:date>2025-10-31T06:54:42+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像基础知识:光学:几何光学:入瞳</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:%E5%85%89%E5%AD%A6:%E5%87%A0%E4%BD%95%E5%85%89%E5%AD%A6:%E5%85%A5%E7%9E%B3&amp;rev=1761893682&amp;do=diff</link>
        <description>入瞳及其在相机成像测试中的应用

当我们观察人眼时，可见一黑色小孔（即瞳孔），所有入射光均通过瞳孔进入人眼。从生理上说，瞳孔是虹膜中央的孔，但我们观察到的并不是瞳孔本身，而是瞳孔通过其前面的屈光结构（如角膜、前房等）所成的像。相似地，如果我们在一个明亮的环境，从正面观察一个照相机镜头，会看到一个明亮的斑，这个斑便是镜头的光圈（通常置于镜片之间）经过其前面的镜片所成的像，称为入射光瞳（以下简称入瞳）。在相机的成像测试中，入瞳是一个十分重要的概念，有着广泛的应用。在本文中，我们就与大家一同来认识入瞳。…</description>
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        <dc:date>2026-01-29T07:53:25+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:cms测试用例:cms_锐度</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:cms%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B:cms_%E9%94%90%E5%BA%A6&amp;rev=1769673205&amp;do=diff</link>
        <description>CMS锐度

CMS为什么要测锐度？


摄像头监控系统CMS（Camera Monitor System）作为传统光学后视镜的电子化替代，通过外部摄像头和舱内显示屏的组合为驾驶员提供车外视野。


而图像锐度（Sharpness）直接决定了CMS成像呈现细节的能力，对行车安全至关重要，直接影响驾驶员能否清晰感知监视器显示的后方来车细节（如：车灯轮廓、车牌、行人、路标等信息）。$$\text{MTF}50_{\langle 1:1 \rangle} \geq \frac{1}{2}\text{MTF}10_{\text{MIN}\langle 1:1 \rangle} \left[ \frac{\text{LW}}{\text{PH}} \right]$$$$\text{MTF}50_{\langle 1:1 \rangle} \geq \frac{1}{2} \times \left( \frac{1}{2} \text{MTF}10_{\text{MIN}\langle 1:1 \rangle} \right) \left[ \frac{\text{LW}}{\text{PH}} …</description>
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        <dc:date>2026-03-09T02:07:51+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:成像质量评价</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:%E6%88%90%E5%83%8F%E8%B4%A8%E9%87%8F%E8%AF%84%E4%BB%B7&amp;rev=1773022071&amp;do=diff</link>
        <description>成像质量评价

 概述

成像质量评价（Image Quality Assessment, IQA）指在给定条件（如相机的被摄场景、照明环境及显示设备的输入等）下，对成像系统的成像性能（如分辨率、噪声、畸变、色彩、动态范围等）进行主客观分析与评估。成像质量直接影响图像的实用价值 —— 例如人类观察者的视觉体验（如欣赏照片或影片）或目视效果（如使用</description>
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    <item rdf:about="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%B7%A5%E5%85%B7:%E5%B9%B3%E8%A1%8C%E5%85%89%E7%AE%A1:%E5%B9%B3%E8%A1%8C%E5%85%89%E7%AE%A1%E7%9A%84%E5%85%89%E7%9E%B3%E5%8C%B9%E9%85%8D&amp;rev=1768891133&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2026-01-20T06:38:53+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>yanding:成像质量评价:工具:平行光管:平行光管的光瞳匹配</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%B7%A5%E5%85%B7:%E5%B9%B3%E8%A1%8C%E5%85%89%E7%AE%A1:%E5%B9%B3%E8%A1%8C%E5%85%89%E7%AE%A1%E7%9A%84%E5%85%89%E7%9E%B3%E5%8C%B9%E9%85%8D&amp;rev=1768891133&amp;do=diff</link>
        <description>平行光管与 DUT 的光瞳匹配

孔径光阑通过其与像之间的光学系统所成的像，称作出射光瞳，简称出瞳。出瞳是光学系统出射光线的公共出口，出瞳中心是像方主光线（或其延长线）的交点。</description>
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        <dc:format>text/html</dc:format>
        <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:format>text/html</dc:format>
        <dc:date>2026-02-26T07:29:56+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>测试用例2</title>
        <link>https://wiki.yanding.com/doku.php?id=%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B2&amp;rev=1772090996&amp;do=diff</link>
        <description>测试课堂

ADAS测试用例

	* 对比度表现指标_cpi

	* 闪烁 flicker

Camera测试用例

	* 动态范围

	* 噪声

	* 均匀性

	* 帧率

	* 曝光时间

	* 灰阶响应

	* 畸变

	* 白平衡

	*  眩光

	* 空间频率响应_sfr

	* 纹理丢失

	* 色差

	* 色彩还原

	* 视场角

	* 防抖

CMS测试用例

	* CMS的介绍

	* CMS视镜类型及视野要求

	* CMS测试前所需参数

	* 亮度对比度复现

	* 灰度等级复现

	* 方向均匀性

	* 横向均匀性

	* 双点光源

	* 眩光

	* 景深

	* 色彩还原

	* 帧率…</description>
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    <item rdf:about="https://wiki.yanding.com/doku.php?id=camera%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B&amp;rev=1768528821&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2026-01-16T02:00:21+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>camera测试用例</title>
        <link>https://wiki.yanding.com/doku.php?id=camera%E6%B5%8B%E8%AF%95%E7%94%A8%E4%BE%8B&amp;rev=1768528821&amp;do=diff</link>
        <description>*空间频率响应_sfr

*纹理丢失

*灰阶响应

*动态范围

*噪声

*视场角

*畸变

*色差

*均匀性

*眩光

*色彩还原

*白平衡

*帧率

*曝光时间

*防抖</description>
    </item>
    <item rdf:about="https://wiki.yanding.com/doku.php?id=keywords&amp;rev=1761726761&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2025-10-29T08:32:41+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>keywords</title>
        <link>https://wiki.yanding.com/doku.php?id=keywords&amp;rev=1761726761&amp;do=diff</link>
        <description>动态范围/色彩还原/空间频率响应/均匀性/畸变/杂光/闪烁/CMS/图卡</description>
    </item>
</rdf:RDF>
