数字图像处理-图像读取与显示、图像融合、图像色调转换
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数字图像处理——图像读取与显示、图像融合、图像色调转换，包括python源代码，作业要求，数字图像处理基础的知识点PPT，代码所有图片示例及转换结果等等。 <link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/bg1.jpg"/><div class="c x0 y1 w2 h0"><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">第二章<span class="_ _0"> </span>数字图像处理基础</div><div class="t m0 x2 h3 y3 ff2 fs1 fc1 sc0 ls0 ws0">第二章<span class="_ _1"> </span>数字图像处理基础</div><div class="t m0 x3 h4 y4 ff3 fs2 fc0 sc0 ls0 ws0">1</div><div class="t m0 x4 h5 y5 ff4 fs3 fc1 sc0 ls1 ws0">2.1 <span class="_ _2"></span><span class="ff5 ls0">图像数字化技术</span></div><div class="t m0 x4 h6 y6 ff4 fs0 fc1 sc0 ls2 ws0">2.2 <span class="ff5 ls3">色度学基础与颜色模型</span></div><div class="t m0 x4 h6 y7 ff4 fs0 fc1 sc0 ls2 ws0">2.3 <span class="ff5 ls3">数字图像类型</span></div><div class="t m0 x4 h6 y8 ff4 fs0 fc1 sc0 ls2 ws0">2.4 <span class="ff5 ls3">图像文件格式</span></div></div></div><div class="pi" data-data='{"ctm":[1.333333,0.000000,0.000000,1.333333,0.000000,0.000000]}'></div></div><div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/bg2.jpg"><div class="c x0 y1 w2 h0"><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">第二章<span class="_ _0"> </span>数字图像处理基础</div><div class="t m0 x5 h7 y9 ff4 fs4 fc0 sc0 ls0 ws0">2.1 <span class="ff5">图像数字化技术</span></div><div class="t m0 x6 h6 ya ff5 fs0 fc0 sc0 ls0 ws0">图像的数字化包括采样和量化两个过程。</div><div class="t m0 x7 h6 yb ff5 fs0 fc0 sc0 ls3 ws0">设连续图像<span class="_ _3"> </span><span class="ff6 ls0">f<span class="_ _3"> </span><span class="ff3">(</span><span class="ls3">x,<span class="_ _4"> </span></span>y<span class="ff3">)<span class="ff5">经数字化后，可以用一个离散量组成的矩</span></span></span></div><div class="t m0 x6 h5 yc ff5 fs3 fc0 sc0 ls0 ws0">阵<span class="_ _0"> </span><span class="ff6">g<span class="_"> </span></span>（<span class="ls2">即二维数组</span>）<span class="ls2">来表示</span>。</div><div class="t m0 x3 h4 y4 ff3 fs2 fc2 sc0 ls0 ws0">2</div></div><div class="c x8 yd w3 h8"><div class="t m1 x2 h9 ye ff3 fs5 fc0 sc0 ls0 ws0">(0<span class="_ _5"></span>,<span class="_ _6"></span>0)<span class="_ _7"> </span>(0<span class="_ _5"></span>,<span class="_ _2"></span>1<span class="_ _8"></span>)<span class="_ _9"> </span><span class="fc3 sc0">(</span><span class="fc3 sc0">0</span><span class="_ _5"></span><span class="fc3 sc0">,</span><span class="_ _a"> </span>1<span class="_ _8"></span>)</div><div class="t m1 x2 h9 yf ff3 fs5 fc0 sc0 ls0 ws0">(<span class="_ _8"></span>1<span class="_ _b"></span>,<span class="_ _6"></span>0)<span class="_ _7"> </span>(<span class="_ _8"></span>1<span class="_ _b"></span>,<span class="_ _2"></span>1<span class="_ _8"></span>)<span class="_ _c"> </span><span class="fc3 sc0">(</span><span class="_ _8"></span><span class="fc3 sc0">1</span><span class="_ _b"></span><span class="fc3 sc0">,</span><span class="_ _a"> </span>1<span class="_ _8"></span>)</div><div class="t m1 x9 h9 y10 ff3 fs5 fc0 sc0 ls0 ws0">(<span class="_ _d"> </span>,<span class="_ _e"> </span>)</div><div class="t m1 x2 h9 y11 ff3 fs5 fc0 sc0 ls0 ws0">(<span class="_ _f"> </span>1<span class="_ _b"></span>,<span class="_ _6"></span>0)<span class="_ _10"> </span>(<span class="_ _f"> </span>1<span class="_ _b"></span>,<span class="_ _11"></span>1<span class="_ _8"></span>)<span class="_ _12"> </span><span class="fc3 sc0">(</span><span class="_ _f"> </span>1<span class="_ _b"></span>,<span class="_ _a"> </span>1<span class="_ _8"></span>)</div><div class="t m1 xa ha ye ff6 fs5 fc0 sc0 ls0 ws0">f<span class="_ _13"> </span>f<span class="_ _14"> </span><span class="fc3 sc0">f</span><span class="_ _15"> </span><span class="fc3 sc0">n</span></div><div class="t m1 xa ha yf ff6 fs5 fc0 sc0 ls0 ws0">f<span class="_ _16"> </span>f<span class="_ _17"> </span><span class="fc3 sc0">f</span><span class="_ _18"> </span><span class="fc3 sc0">n</span></div><div class="t m1 xb ha y10 ff6 fs5 fc0 sc0 ls0 ws0">g<span class="_ _19"> </span>i<span class="_ _1a"> </span>j</div><div class="t m1 xa ha y11 ff6 fs5 fc0 sc0 ls0 ws0">f<span class="_ _1b"> </span>m<span class="_ _1c"> </span>f<span class="_ _1b"> </span>m<span class="_ _1d"> </span><span class="fc3 sc0">f</span><span class="_ _1b"> </span><span class="fc3 sc0">m</span><span class="_ _1e"> </span>n</div><div class="t m1 xc hb y12 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 xd hb y13 ff7 fs5 fc0 sc0 ls0 ws0">−</div><div class="t m1 xc hb y14 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 xe hb y15 ff7 fs5 fc0 sc0 ls0 ws0">−</div><div class="t m1 xc hb y16 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 x7 hb y10 ff7 fs5 fc0 sc0 ls0 ws0">=</div><div class="t m1 xc hb y17 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 xc hb y18 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 xc hb y19 ff7 fs5 fc0 sc0 ls4 ws0"></div><div class="t m1 xf hb y11 ff7 fs5 fc0 sc0 ls0 ws0">−<span class="_ _1f"> </span>−<span class="_ _20"> </span>−<span class="_ _21"> </span>−</div><div class="t m1 xc hb y1a ff7 fs5 fc0 sc0 ls4 ws0"></div></div></div><div class="pi" data-data='{"ctm":[1.333333,0.000000,0.000000,1.333333,0.000000,0.000000]}'></div></div><div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/bg3.jpg"><div class="c x0 y1 w2 h0"><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0"><span class="fc3 sc0">第二</span>章<span class="_ _0"> </span>数字图像处理基础</div><div class="t m0 x3 h4 y4 ff3 fs2 fc0 sc0 ls0 ws0">3</div><div class="t m0 x10 hc y1b ff3 fs3 fc0 sc0 ls5 ws0">215<span class="ff8 ls0">×</span>150</div></div></div><div class="pi" data-data='{"ctm":[1.333333,0.000000,0.000000,1.333333,0.000000,0.000000]}'></div></div><div id="pf4" class="pf w0 h0" data-page-no="4"><div class="pc pc4 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/bg4.jpg"><div class="c x0 y1 w2 h0"><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">第二章<span class="_ _0"> </span>数字图像处理基础</div><div class="t m0 x7 hc y1c ff8 fs3 fc0 sc0 ls0 ws0">矩阵中的每一个元素称为像元<span class="_ _5"></span>、<span class="ls2">像素或图像元素</span>。而<span class="ff6">g<span class="_ _d"> </span><span class="ff3">(</span><span class="ls6">i,<span class="_ _22"> </span></span>j<span class="ff3">)</span></span></div><div class="t m0 x6 hd y1d ff8 fs0 fc0 sc0 ls0 ws0">代表<span class="ff3">(<span class="ff6 ls7">i,<span class="_"> </span><span class="ls0">j</span></span>)</span>点的灰度值，即亮度值。</div><div class="t m0 x11 he y1e ff8 fs3 fc0 sc0 ls0 ws0">以上数字化有以下几点说明：</div><div class="t m0 x12 hd y1f ff8 fs0 fc0 sc0 ls0 ws0">（<span class="ff3">1</span>）<span class="_ _23"> </span>由于<span class="ff6">g<span class="_"> </span><span class="ff3">(</span>i, j <span class="ff3 ls8">) </span></span>代表该点图像的光强度，而光是能量的一</div><div class="t m0 x6 hc y20 ff8 fs3 fc0 sc0 ls2 ws0">种形式，故<span class="ff6 ls0">g<span class="_"> </span><span class="ff3">(</span>i, j <span class="ff3 ls9">) </span><span class="ff8">必须大于零，且为有限值，即：</span></span></div><div class="t m0 x13 hd y21 ff3 fs0 fc0 sc0 ls0 ws0">0<span class="ff8">＜<span class="ff6">g<span class="_"> </span></span></span>(<span class="ff6">i, j</span>)<span class="ff8">＜<span class="ff9">∞</span>。</span></div><div class="t m0 x3 h4 y4 ff3 fs2 fc2 sc0 ls0 ws0">4</div></div></div><div class="pi" data-data='{"ctm":[1.333333,0.000000,0.000000,1.333333,0.000000,0.000000]}'></div></div><div id="pf5" class="pf w0 h0" data-page-no="5"><div class="pc pc5 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89659310/bg5.jpg"><div class="c x0 y1 w2 h0"><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">第二章<span class="_ _0"> </span>数字图像处理基础</div></div><div class="c x14 y22 w4 hf"><div class="t m2 x15 h10 y23 ffa fs6 fc0 sc0 ls0 ws0">(a)<span class="_ _24"> </span>(<span class="_ _5"></span>b<span class="_ _2"></span>)</div></div><div class="c x0 y1 w2 h0"><div class="t m0 x16 hd y24 ff8 fs0 fc0 sc0 ls0 ws0">（<span class="ff3">2</span>）<span class="_ _25"> </span>数字化采样一般是按正方形点阵取样的，<span class="_ _25"> </span><span class="ls3">除此之外还有</span></div><div class="t m0 x9 h11 y25 ff8 fs0 fc0 sc0 ls0 ws0">三角形点阵、正六角形点阵取样。</div><div class="t m0 x16 hd y26 ff8 fs0 fc0 sc0 ls0 ws0">（<span class="ff3">3</span>）用<span class="ff6">g<span class="_ _26"> </span><span class="ff3">(</span><span class="ls7">i,<span class="_ _27"> </span></span>j<span class="ff3">)</span></span>的数值来表示<span class="ff3">(<span class="ff6 ls7">i,<span class="_ _27"> </span><span class="ls0">j</span></span>)</span>位置点上灰度级值的大小，即</div><div class="t m0 x9 he y27 ff8 fs3 fc0 sc0 ls0 ws0">只<span class="_ _2"></span>反<span class="_ _2"></span>映<span class="_ _2"></span>了<span class="_ _2"></span>黑<span class="_ _2"></span>白<span class="_ _2"></span>灰<span class="_ _11"></span>度<span class="_ _2"></span>的<span class="_ _2"></span>关<span class="_ _2"></span>系<span class="_ _11"></span>，<span class="_ _28"> </span>如<span class="_ _2"></span>果是<span class="_ _11"></span>一<span class="_ _2"></span>幅<span class="_ _2"></span>彩<span class="_ _2"></span>色<span class="_ _2"></span>图<span class="_ _2"></span>像<span class="_ _11"></span>，<span class="_ _28"> </span>各<span class="_ _2"></span>点<span class="_ _2"></span>的<span class="_ _2"></span>数<span class="_ _2"></span>值</div><div class="t m0 x9 hd y28 ff8 fs0 fc0 sc0 ls0 ws0">还应当反映色彩的变化，可用<span class="ff3">g<span class="_ _19"> </span>(<span class="ff6 ls7">i,<span class="_ _26"> </span>j,<span class="_ _19"> </span></span><span class="ffb">λ</span>)</span>表示，其中<span class="ff9">λ</span><span class="ls3">是波长</span>。如果</div><div class="t m0 x9 hc y29 ff8 fs3 fc0 sc0 ls2 ws0">图像是运动的<span class="ls0">，</span>还应是时间<span class="ff3 ls0">t</span>的函数<span class="ls0">，</span>即可表示为<span class="ff6 ls0">g<span class="_"> </span><span class="ff3">(</span><span class="lsa">i,<span class="_ _23"> </span><span class="ls6">j,<span class="_ _29"> </span></span></span><span class="ffb">λ<span class="ff3">,<span class="_"> </span></span></span>t<span class="ff3">)<span class="ff8">。</span></span></span></div><div class="t m0 x3 h4 y4 ff3 fs2 fc2 sc0 ls0 ws0">5</div></div></div><div class="pi" data-data='{"ctm":[1.333333,0.000000,0.000000,1.333333,0.000000,0.000000]}'></div></div>