/en/series/computer-vision-series/Recent content in Computer Vision Series on Mi&Bee BlogHugo -- gohugo.ioen蓝宝石的傻话Fri, 08 May 2026 10:00:00 +0800/en/posts/physical-world/image-basics-opencv/Fri, 08 May 2026 10:00:00 +0800/en/posts/physical-world/image-basics-opencv/<h2 id="what-is-a-digital-image">What Is a Digital Image</h2> <p>Computer vision operates on digital images. At its core, a digital image is just a 2D array of pixels.</p> <h3 id="pixels-and-grayscale-images">Pixels and Grayscale Images</h3> <p>A grayscale image is the simplest form—each pixel stores a single brightness value from 0 (pure black) to 255 (pure white). In Python, a grayscale image of width W and height H is a 2D array with shape <code>(H, W)</code>:</p> <div class="code-block-wrapper" data-lang="python"> <div class="code-block-header"> <div class="code-block-meta"><span class="code-language">python</span></div> <button class="copy-button" aria-label="Copy code"> <svg class="copy-icon" xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg> <svg class="check-icon" xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="20 6 9 17 4 12"/></svg> </button> </div> <div class="code-block-body"><div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span><span class="lnt">2 </span><span class="lnt">3 </span><span class="lnt">4 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"><span class="line"><span class="cl"><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> </span></span><span class="line"><span class="cl"> </span></span><span class="line"><span class="cl"><span class="c1"># Create a 100x100 gray square (brightness 128)</span> </span></span><span class="line"><span class="cl"><span class="n">gray_img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">),</span> <span class="mi">128</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span></span></span></code></pre></td></tr></table> </div> </div></div> </div><p><code>uint8</code> ranges from 0 to 255 because 8 bits can represent 2^8 = 256 unique values. If a pixel value exceeds its range, <strong>wrap around</strong> occurs: 255 + 1 becomes 0, not 256 (like an odometer rolling over). Use <code>cv2.add()</code> (saturating arithmetic) or <code>np.clip()</code> to prevent wrap around.</p>