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是怎么压缩图片的?</span></a><ol class=nav-child><li class="nav-item nav-level-2"><a class=nav-link href=#1-RGB-%E8%BD%AC%E6%88%90-YCbCr><span class=nav-number>1.1.</span> <span class=nav-text>1. RGB 转成 YCbCr</span></a><li class="nav-item nav-level-2"><a class=nav-link href=#2-%E8%89%B2%E5%BA%A6%E6%8A%BD%E6%A0%B7><span class=nav-number>1.2.</span> <span class=nav-text>2. 色度抽样</span></a><ol class=nav-child><li class="nav-item nav-level-3"><a class=nav-link href=#YCbCr-%E6%98%AF%E5%95%A5%E6%84%8F%E6%80%9D><span class=nav-number>1.2.1.</span> <span class=nav-text>YCbCr 是啥意思</span></a><li class="nav-item nav-level-3"><a class=nav-link href=#%E4%B8%BA%E4%BB%80%E4%B9%88%E5%8F%AF%E4%BB%A5%E6%8A%8A%E4%BA%AE%E5%BA%A6%E5%92%8C%E9%A2%9C%E8%89%B2%E5%88%86%E5%BC%80%EF%BC%9F><span class=nav-number>1.2.2.</span> <span class=nav-text>为什么可以把亮度和颜色分开?</span></a><li class="nav-item nav-level-3"><a class=nav-link href=#4-RGB-%E8%BD%AC-YCbCr-%E6%98%AF%E6%80%8E%E4%B9%88%E8%BD%AC><span class=nav-number>1.2.3.</span> <span class=nav-text>4. RGB 转 YCbCr 是怎么转</span></a><li class="nav-item nav-level-3"><a class=nav-link href=#%E5%88%9A%E6%89%8D%E8%AF%B4%E7%9A%84-4-4-4%E3%80%814-2-2%E3%80%814-2-0-%E6%98%AF%E5%95%A5%E6%84%8F%E6%80%9D><span class=nav-number>1.2.4.</span> <span class=nav-text>刚才说的 4:4:4、4:2:2、4:2:0 是啥意思</span></a></ol><li class="nav-item nav-level-2"><a class=nav-link href=#6-4-4-4%EF%BC%9A%E5%AE%8C%E5%85%A8%E4%B8%8D%E5%87%8F%E5%B0%91%E9%A2%9C%E8%89%B2%E4%BF%A1%E6%81%AF><span class=nav-number>1.3.</span> <span class=nav-text>6. 4:4:4:完全不减少颜色信息</span></a><li class="nav-item nav-level-2"><a class=nav-link href=#7-4-2-2%EF%BC%9A%E6%A8%AA%E5%90%91%E5%87%8F%E5%B0%91%E9%A2%9C%E8%89%B2%E4%BF%A1%E6%81%AF><span class=nav-number>1.4.</span> <span class=nav-text>7. 4:2:2:横向减少颜色信息</span></a><li class="nav-item nav-level-2"><a class=nav-link href=#8-4-2-0%EF%BC%9A%E6%A8%AA%E5%90%91%E5%92%8C%E7%BA%B5%E5%90%91%E9%83%BD%E5%87%8F%E5%B0%91%E9%A2%9C%E8%89%B2%E4%BF%A1%E6%81%AF><span class=nav-number>1.5.</span> <span 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itemprop=mainEntityOfPage><span hidden itemprop=author itemscope itemtype=http://schema.org/Person><meta content=/uploads/avatar.jpg itemprop=image><meta content=Nicksxs itemprop=name></span><span hidden itemprop=publisher itemscope itemtype=http://schema.org/Organization><meta content="Nicksxs's Blog" itemprop=name><meta content="Nicksxs 的技术博客,深入 Java 运行时与生产诊断、低成本大模型推理和 Agent 工程实践。" itemprop=description></span><span hidden itemprop=post itemscope itemtype=http://schema.org/CreativeWork><meta content="JPEG 图片格式详解:压缩原理、DCT、量化与编码流程 | Nicksxs's Blog" itemprop=name><meta content="本文系统讲解 JPEG 有损压缩流程,包括 RGB 到 YCbCr、色度抽样、8×8 分块、DCT、量化、Zigzag 扫描和熵编码,并说明压缩率与画质之间的取舍。" itemprop=description></span><header class=post-header><h1 itemprop="name headline" class=post-title>JPEG 图片格式详解:压缩原理、DCT、量化与编码流程</h1><div class=post-meta-container><div class=post-meta><span class=post-meta-item><span class=post-meta-item-icon><i class="far fa-calendar"></i> </span><span class=post-meta-item-text>发表于</span> <time itemprop="dateCreated datePublished" title="创建时间:2026-06-21 20:42:27" datetime=2026-06-21T20:42:27+08:00>2026-06-21</time> </span><span class=post-meta-item><span class=post-meta-item-icon><i class="far fa-folder"></i> </span><span class=post-meta-item-text>分类于</span> <span itemprop=about itemscope itemtype=http://schema.org/Thing><a href=/categories/%E7%AE%97%E6%B3%95/ itemprop=url rel=index><span itemprop=name>算法</span></a> </span></span><span class="post-meta-item cloudflare-page-counter" data-title="JPEG 图片格式详解:压缩原理、DCT、量化与编码流程" data-increment=true data-path=/2026/06/21/%E6%B5%85%E6%9E%90%E4%B8%80%E4%B8%8B%E5%90%84%E7%B1%BB%E5%9B%BE%E7%89%87%E6%A0%BC%E5%BC%8F%E5%8F%8A%E5%85%B6%E6%9D%A5%E6%BA%90/ title=阅读次数><span class=post-meta-item-icon><i class="far fa-eye"></i> </span><span class=post-meta-item-text>阅读次数:</span> <span class=cloudflare-page-counter-count></span></span></div><div class=post-description>本文系统讲解 JPEG 有损压缩流程,包括 RGB 到 YCbCr、色度抽样、8×8 分块、DCT、量化、Zigzag 扫描和熵编码,并说明压缩率与画质之间的取舍。</div></div></header><div class=post-body itemprop=articleBody><h1 id=JPEG-是怎么压缩图片的?><a title="JPEG 是怎么压缩图片的?" class=headerlink href=#JPEG-是怎么压缩图片的?></a>JPEG 是怎么压缩图片的?</h1><p>JPEG 的核心目标是:<blockquote><p>在人眼不太容易察觉的地方丢掉一些信息,从而大幅减小照片体积。</blockquote><p>所以 JPEG 通常是 <strong>有损压缩</strong>。它不是简单地把文件“打包变小”,而是会真的改变图像数据。<p>可以把 JPEG 压缩理解成几个步骤:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br><span class=line>7</span><br><span class=line>8</span><br><span class=line>9</span><br><span class=line>10</span><br><span class=line>11</span><br><span class=line>12</span><br><span class=line>13</span><br><span class=line>14</span><br><span class=line>15</span><br><span class=line>16</span><br><span class=line>17</span><br><span class=line>18</span><br><span class=line>19</span><br></pre><td class=code><pre><span class=line>RGB 图像</span><br><span class=line>↓</span><br><span class=line>转换成 YCbCr</span><br><span class=line>↓</span><br><span class=line>色度抽样</span><br><span class=line>↓</span><br><span class=line>切成 8×8 小块</span><br><span class=line>↓</span><br><span class=line>DCT 变换</span><br><span class=line>↓</span><br><span class=line>量化</span><br><span class=line>↓</span><br><span class=line>Zigzag 扫描</span><br><span class=line>↓</span><br><span class=line>游程编码</span><br><span class=line>↓</span><br><span class=line>熵编码</span><br><span class=line>↓</span><br><span class=line>生成 JPEG 文件</span><br></pre></table></figure><hr><h2 id=1-RGB-转成-YCbCr><a title="1. RGB 转成 YCbCr" class=headerlink href=#1-RGB-转成-YCbCr></a>1. RGB 转成 YCbCr</h2><p>我们平时看到的图片通常可以理解成 RGB:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>R = 红色</span><br><span class=line>G = 绿色</span><br><span class=line>B = 蓝色</span><br></pre></table></figure><p>但 JPEG 不直接用 RGB 压缩,而是会先转换成 YCbCr:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>Y = 亮度信息</span><br><span class=line>Cb = 蓝色色度信息</span><br><span class=line>Cr = 红色色度信息</span><br></pre></table></figure><p>这么做是因为人眼对 <strong>亮度变化</strong> 很敏感,但对 <strong>颜色细节</strong> 没那么敏感。<p>比如一张人脸照片:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>轮廓、明暗、边缘变化很重要</span><br><span class=line>颜色细节稍微模糊一点,人眼不一定明显察觉</span><br></pre></table></figure><p>所以 JPEG 会把图像拆成:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>更重要的亮度通道 Y</span><br><span class=line>没那么重要的颜色通道 Cb / Cr</span><br></pre></table></figure><p>后面压缩时,颜色通道可以压得更狠一些。<hr><h2 id=2-色度抽样><a title="2. 色度抽样" class=headerlink href=#2-色度抽样></a>2. 色度抽样</h2><p>既然人眼对颜色细节没那么敏感,JPEG 就可以减少颜色信息的采样数量。<p>常见色度抽样有:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>4:4:4 不减少颜色信息</span><br><span class=line>4:2:2 横向减少一半颜色信息</span><br><span class=line>4:2:0 横向和纵向都减少颜色信息</span><br></pre></table></figure><p>最常见的是 <strong>4:2:0</strong>。<p>它大概意思是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>亮度信息完整保留</span><br><span class=line>颜色信息减少到原来的一部分</span><br></pre></table></figure><p>举个简化例子:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br></pre><td class=code><pre><span class=line>原始:</span><br><span class=line>每个像素都有 Y、Cb、Cr</span><br><span class=line></span><br><span class=line>4:2:0 后:</span><br><span class=line>每个像素仍然有 Y</span><br><span class=line>但多个像素共用一组 Cb、Cr</span><br></pre></table></figure><p>这一步对照片很有效,因为自然照片里颜色通常是连续变化的。<br>但如果是文字截图、UI 图标、红蓝边缘特别明显的图,色度抽样可能会让边缘发糊、出现彩边。<p>所以:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>照片适合 JPEG</span><br><span class=line>截图、文字、Logo 不太适合 JPEG</span><br></pre></table></figure><p>这里再补充一个,就是4:2:0究竟是啥意思<h3 id=YCbCr-是啥意思><a title="YCbCr 是啥意思" class=headerlink href=#YCbCr-是啥意思></a>YCbCr 是啥意思</h3><p>YCbCr 会把一个颜色拆成三部分:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>Y = 亮度,也就是明暗</span><br><span class=line>Cb = 蓝色色度差,大概表示“偏蓝还是不偏蓝”</span><br><span class=line>Cr = 红色色度差,大概表示“偏红还是不偏红”</span><br></pre></table></figure><p>注意:Cb / Cr 不是直接等于蓝色和红色,而是 <strong>颜色差异信息</strong>。<p>可以粗略理解为:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>Y 管黑白明暗</span><br><span class=line>Cb 管蓝黄方向的颜色变化</span><br><span class=line>Cr 管红绿方向的颜色变化</span><br></pre></table></figure><p>所以一张 RGB 图片转成 YCbCr 后,可以想象成三张灰度图:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br></pre><td class=code><pre><span class=line>原图</span><br><span class=line>↓</span><br><span class=line>Y 图:黑白版,保留轮廓、明暗、细节</span><br><span class=line>Cb 图:颜色偏蓝 / 偏黄的信息</span><br><span class=line>Cr 图:颜色偏红 / 偏绿的信息</span><br></pre></table></figure><p>其中最重要的是 <strong>Y 亮度图</strong>。<hr><h3 id=为什么可以把亮度和颜色分开?><a class=headerlink href=#为什么可以把亮度和颜色分开? title=为什么可以把亮度和颜色分开?></a>为什么可以把亮度和颜色分开?</h3><p>因为人眼看图时,最敏感的是亮度边缘,而不是颜色边缘。<p>比如一张白底黑字图片:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>白底 + 黑字</span><br></pre></table></figure><p>你能很清楚看见文字,是因为亮度差异很大。<p>再比如一张人像照片:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br></pre><td class=code><pre><span class=line>脸部轮廓</span><br><span class=line>鼻梁阴影</span><br><span class=line>眼睛边缘</span><br><span class=line>头发明暗</span><br><span class=line>衣服褶皱</span><br></pre></table></figure><p>这些主要靠 <strong>Y 亮度信息</strong> 表达。<p>但颜色细节稍微粗糙一点,比如皮肤颜色、天空蓝色、墙面颜色,人的感知没那么敏锐。<p>所以 JPEG 的策略是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>Y 亮度:尽量保留清楚</span><br><span class=line>Cb / Cr 颜色:可以减少一些</span><br></pre></table></figure><p>这就是色度抽样的基础。<hr><h3 id=4-RGB-转-YCbCr-是怎么转><a title="4. RGB 转 YCbCr 是怎么转" class=headerlink href=#4-RGB-转-YCbCr-是怎么转></a>4. RGB 转 YCbCr 是怎么转</h3><p>近似公式是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>Y = 0.299R + 0.587G + 0.114B</span><br><span class=line>Cb = B - Y 的某种缩放</span><br><span class=line>Cr = R - Y 的某种缩放</span><br></pre></table></figure><p>这里可以看到G是权重最大的,因为人眼对绿色最敏感,所以绿色对亮度感知贡献最大。<p>例如:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>R = 200</span><br><span class=line>G = 120</span><br><span class=line>B = 80</span><br></pre></table></figure><p>那么亮度 Y 大概是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>Y = 0.299 × 200 + 0.587 × 120 + 0.114 × 80</span><br><span class=line> ≈ 59.8 + 70.4 + 9.1</span><br><span class=line> ≈ 139.3</span><br></pre></table></figure><p>所以这个像素的亮度大概是 139。<p>然后 Cb / Cr 负责记录它相对于这个亮度来说,颜色偏向哪里。<p>简单理解:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>Y 记录:这个点有多亮</span><br><span class=line>Cb/Cr 记录:在这个亮度基础上,它是什么颜色</span><br></pre></table></figure><hr><h3 id=刚才说的-4-4-4、4-2-2、4-2-0-是啥意思><a title="刚才说的 4:4:4、4:2:2、4:2:0 是啥意思" class=headerlink href=#刚才说的-4-4-4、4-2-2、4-2-0-是啥意思></a>刚才说的 4:4:4、4:2:2、4:2:0 是啥意思</h3><blockquote><p>色度通道 Cb / Cr 相对于亮度通道 Y,被保留了多少采样点。</blockquote><p>先看一个 2×2 像素块。<p>原始情况下,每个像素都有:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>Y + Cb + Cr</span><br></pre></table></figure><p>也就是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br></pre><td class=code><pre><span class=line>像素 A: Y1 Cb1 Cr1</span><br><span class=line>像素 B: Y2 Cb2 Cr2</span><br><span class=line>像素 C: Y3 Cb3 Cr3</span><br><span class=line>像素 D: Y4 Cb4 Cr4</span><br></pre></table></figure><hr><h2 id=6-4-4-4:完全不减少颜色信息><a title="6. 4:4:4:完全不减少颜色信息" class=headerlink href=#6-4-4-4:完全不减少颜色信息></a>6. 4:4:4:完全不减少颜色信息</h2><p>4:4:4 表示:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>每个像素都有自己的 Y</span><br><span class=line>每个像素也都有自己的 Cb / Cr</span><br></pre></table></figure><p>用 2×2 看:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br><span class=line>7</span><br><span class=line>8</span><br><span class=line>9</span><br><span class=line>10</span><br><span class=line>11</span><br></pre><td class=code><pre><span class=line>Y:</span><br><span class=line>Y1 Y2</span><br><span class=line>Y3 Y4</span><br><span class=line></span><br><span class=line>Cb:</span><br><span class=line>Cb1 Cb2</span><br><span class=line>Cb3 Cb4</span><br><span class=line></span><br><span class=line>Cr:</span><br><span class=line>Cr1 Cr2</span><br><span class=line>Cr3 Cr4</span><br></pre></table></figure><p>也就是亮度和颜色分辨率一样高。<p>所以:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>4:4:4 = 不做色度抽样</span><br></pre></table></figure><p>质量最好,体积也更大。<hr><h2 id=7-4-2-2:横向减少颜色信息><a title="7. 4:2:2:横向减少颜色信息" class=headerlink href=#7-4-2-2:横向减少颜色信息></a>7. 4:2:2:横向减少颜色信息</h2><p>4:2:2 表示:<blockquote><p>水平方向的颜色采样减半,垂直方向不减。</blockquote><p>可以理解成:横向相邻两个像素共用一组 Cb / Cr。<p>比如 2×2 像素:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br><span class=line>7</span><br><span class=line>8</span><br><span class=line>9</span><br><span class=line>10</span><br><span class=line>11</span><br></pre><td class=code><pre><span class=line>Y:</span><br><span class=line>Y1 Y2</span><br><span class=line>Y3 Y4</span><br><span class=line></span><br><span class=line>Cb:</span><br><span class=line>Cb1 Cb1</span><br><span class=line>Cb2 Cb2</span><br><span class=line></span><br><span class=line>Cr:</span><br><span class=line>Cr1 Cr1</span><br><span class=line>Cr2 Cr2</span><br></pre></table></figure><p>也就是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>第一行:两个像素共用一组颜色</span><br><span class=line>第二行:两个像素共用一组颜色</span><br></pre></table></figure><p>亮度 Y 仍然每个像素都有。<p>所以:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>4:2:2 = 横向颜色分辨率减半,纵向颜色分辨率不变</span><br></pre></table></figure><p>如果原来颜色采样是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>宽 1000,高 1000</span><br></pre></table></figure><p>4:2:2 的颜色通道大概变成:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>宽 500,高 1000</span><br></pre></table></figure><hr><h2 id=8-4-2-0:横向和纵向都减少颜色信息><a title="8. 4:2:0:横向和纵向都减少颜色信息" class=headerlink href=#8-4-2-0:横向和纵向都减少颜色信息></a>8. 4:2:0:横向和纵向都减少颜色信息</h2><p>4:2:0 最容易误解。它不是说“颜色没有了”,也不是说“第二行没有颜色”。<p>它的意思是:<blockquote><p>色度信息在横向减半,纵向也减半。</blockquote><p>也就是一个 2×2 像素块共用一组 Cb / Cr。<p>看 2×2:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br><span class=line>7</span><br><span class=line>8</span><br><span class=line>9</span><br><span class=line>10</span><br><span class=line>11</span><br></pre><td class=code><pre><span class=line>Y:</span><br><span class=line>Y1 Y2</span><br><span class=line>Y3 Y4</span><br><span class=line></span><br><span class=line>Cb:</span><br><span class=line>Cb1 Cb1</span><br><span class=line>Cb1 Cb1</span><br><span class=line></span><br><span class=line>Cr:</span><br><span class=line>Cr1 Cr1</span><br><span class=line>Cr1 Cr1</span><br></pre></table></figure><p>也就是说:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br></pre><td class=code><pre><span class=line>4 个像素各自有自己的亮度 Y</span><br><span class=line>但 4 个像素共用同一组颜色 Cb / Cr</span><br></pre></table></figure><p>所以颜色通道的分辨率变成原来的:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>宽度 1/2</span><br><span class=line>高度 1/2</span><br><span class=line>总采样点 = 1/4</span><br></pre></table></figure><p>假设原图是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>1920 × 1080</span><br></pre></table></figure><p>Y 通道仍然是:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>1920 × 1080</span><br></pre></table></figure><p>但 Cb 通道变成:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>960 × 540</span><br></pre></table></figure><p>Cr 通道也变成:<figure class="highlight text"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>960 × 540</span><br></pre></table></figure><p>这就是“横向纵向都减少颜色信息”。<hr><p>这是一个前置的理解,那么关于图片格式,也想聊下怎么识别这些格式,光是后缀好像是可以被随意改动,比如这个jpeg的格式,那么我们可以从文件头来看<figure class="highlight plaintext"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>FF D8 FF E0 ... 4A 46 49 46</span><br></pre></table></figure><p>后面就代表的是 <code>JFIF</code> 这是文件头<p>我们也可以用一个小工具来识别<figure class="highlight php"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br><span class=line>7</span><br><span class=line>8</span><br><span class=line>9</span><br><span class=line>10</span><br><span class=line>11</span><br><span class=line>12</span><br><span class=line>13</span><br><span class=line>14</span><br><span class=line>15</span><br><span class=line>16</span><br><span class=line>17</span><br><span class=line>18</span><br><span class=line>19</span><br><span class=line>20</span><br><span class=line>21</span><br><span class=line>22</span><br><span class=line>23</span><br><span class=line>24</span><br><span class=line>25</span><br><span class=line>26</span><br><span class=line>27</span><br><span class=line>28</span><br><span class=line>29</span><br><span class=line>30</span><br><span class=line>31</span><br><span class=line>32</span><br><span class=line>33</span><br><span class=line>34</span><br><span class=line>35</span><br><span class=line>36</span><br><span class=line>37</span><br><span class=line>38</span><br><span class=line>39</span><br><span class=line>40</span><br><span class=line>41</span><br><span class=line>42</span><br><span class=line>43</span><br><span class=line>44</span><br><span class=line>45</span><br><span class=line>46</span><br></pre><td class=code><pre><span class=line><span class=meta>&LT?php</span></span><br><span class=line></span><br><span class=line><span class=function><span class=keyword>function</span> <span class=title>detectImageType</span>(<span class=params><span class=keyword>string</span> <span class=variable>$path</span></span>): <span class=title>string</span></span></span><br><span class=line><span class=function></span>{</span><br><span class=line> <span class=variable>$h</span> = <span class="title function_ invoke__">file_get_contents</span>(<span class=variable>$path</span>, <span class=literal>false</span>, <span class=literal>null</span>, <span class=number>0</span>, <span class=number>32</span>);</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class=variable>$h</span> === <span class=literal>false</span> || <span class=variable>$h</span> === <span class=string>''</span>) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'unknown'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">strncmp</span>(<span class=variable>$h</span>, <span class=string>"\xFF\xD8\xFF"</span>, <span class=number>3</span>) === <span class=number>0</span>) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/jpeg'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">strncmp</span>(<span class=variable>$h</span>, <span class=string>"\x89PNG\x0D\x0A\x1A\x0A"</span>, <span class=number>8</span>) === <span class=number>0</span>) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/png'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">strncmp</span>(<span class=variable>$h</span>, <span class=string>"GIF87a"</span>, <span class=number>6</span>) === <span class=number>0</span> || <span class="title function_ invoke__">strncmp</span>(<span class=variable>$h</span>, <span class=string>"GIF89a"</span>, <span class=number>6</span>) === <span class=number>0</span>) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/gif'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">strlen</span>(<span class=variable>$h</span>) >= <span class=number>12</span> && <span class="title function_ invoke__">substr</span>(<span class=variable>$h</span>, <span class=number>0</span>, <span class=number>4</span>) === <span class=string>"RIFF"</span> && <span class="title function_ invoke__">substr</span>(<span class=variable>$h</span>, <span class=number>8</span>, <span class=number>4</span>) === <span class=string>"WEBP"</span>) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/webp'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">strlen</span>(<span class=variable>$h</span>) >= <span class=number>12</span> && <span class="title function_ invoke__">substr</span>(<span class=variable>$h</span>, <span class=number>4</span>, <span class=number>4</span>) === <span class=string>"ftyp"</span>) {</span><br><span class=line> <span class=variable>$brands</span> = <span class="title function_ invoke__">substr</span>(<span class=variable>$h</span>, <span class=number>8</span>);</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (<span class="title function_ invoke__">str_contains</span>(<span class=variable>$brands</span>, <span class=string>"avif"</span>)) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/avif'</span>;</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>if</span> (</span><br><span class=line> <span class="title function_ invoke__">str_contains</span>(<span class=variable>$brands</span>, <span class=string>"heic"</span>) ||</span><br><span class=line> <span class="title function_ invoke__">str_contains</span>(<span class=variable>$brands</span>, <span class=string>"heix"</span>) ||</span><br><span class=line> <span class="title function_ invoke__">str_contains</span>(<span class=variable>$brands</span>, <span class=string>"mif1"</span>)</span><br><span class=line> ) {</span><br><span class=line> <span class=keyword>return</span> <span class=string>'image/heif'</span>;</span><br><span class=line> }</span><br><span class=line> }</span><br><span class=line></span><br><span class=line> <span class=keyword>return</span> <span class=string>'unknown'</span>;</span><br><span class=line>}</span><br><span class=line></span><br><span class=line><span class=keyword>echo</span> <span class="title function_ invoke__">detectImageType</span>(<span class=variable>$argv</span>[<span class=number>1</span>] ?? <span class=string>''</span>) . PHP_EOL;</span><br></pre></table></figure><p>这是通过文件头和brand来一起识别,brand是针对那些跟视频格式一致的可能包含容器的格式<br>比如<code>HEIC / AVIF</code>,对于<code>JPEG、PNG、GIF、WebP</code>这类常规格式,是一般从文件头识别<br>而后面的容器型则需要结合容器的brand标识,<br>比如一个<code>AVIF</code>的文件头是<figure class="highlight plaintext"><table><tr><td class=gutter><pre><span class=line>1</span><br></pre><td class=code><pre><span class=line>00 00 00 20 66 74 79 70 61 76 69 66 00 00 00 00 61 76 69 66 6D 69 66 31</span><br></pre></table></figure><p>拆开以后就是<figure class="highlight plaintext"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br><span class=line>4</span><br><span class=line>5</span><br><span class=line>6</span><br></pre><td class=code><pre><span class=line>00 00 00 20 = box size</span><br><span class=line>66 74 79 70 = ftyp</span><br><span class=line>61 76 69 66 = avif</span><br><span class=line>00 00 00 00 = minor_version</span><br><span class=line>61 76 69 66 = avif</span><br><span class=line>6D 69 66 31 = mif1</span><br></pre></table></figure><p>也就是<figure class="highlight plaintext"><table><tr><td class=gutter><pre><span class=line>1</span><br><span class=line>2</span><br><span class=line>3</span><br></pre><td class=code><pre><span class=line>box type: ftyp</span><br><span class=line>major_brand: avif</span><br><span class=line>compatible_brands: avif, mif1</span><br></pre></table></figure><p>这样就大致知道了图片格式的识别</div><footer class=post-footer><div class="affiliate-creative affiliate-creative--post-end" data-affiliate-id=tencent-cloud-general><a rel="sponsored noopener" aria-label=腾讯云产品优惠 href=https://cloud.tencent.com/act/cps/redirect?redirect=2446&cps_key=2e33a1eedb380997d03618b4a5ba6ca7&from=console target=_blank><img alt=腾讯云服务器、数据库和云产品优惠 decoding=async height=419 loading=lazy src=/uploads/affiliate/tencent-cloud-general.webp width=690> </a><span class=affiliate-disclosure>推广</span></div><div class=reward-container><div>请我一杯咖啡吧!</div><button>赞赏</button><div 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