<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8">
<meta name="generator" content="pdf2htmlEX">
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
<link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css">
<link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css">
<link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/625d1a16be9ad24cfa789309/raw.css">
<script src="https://static.pudn.com/base/js/compatibility.min.js"></script>
<script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script>
<script>
try{
pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({});
}catch(e){}
</script>
<title></title>
</head>
<body>
<div id="sidebar" style="display: none">
<div id="outline">
</div>
</div>
<div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/625d1a16be9ad24cfa789309/bg1.jpg"><div class="c x0 y1 w2 h2"><div class="t m0 x1 h3 y2 ff1 fs0 fc0 sc0 ls0 ws0">图像融合实验</div><div class="t m0 x2 h4 y3 ff2 fs1 fc0 sc1 ls0 ws0"> </div><div class="t m0 x3 h5 y4 ff1 fs2 fc0 sc0 ls0 ws0">课堂教学中共提及如下几种方法<span class="sc1">:</span></div><div class="t m0 x2 h5 y5 ff3 fs2 fc0 sc1 ls0 ws0">(1)<span class="_ _0"></span><span class="ff1">简单的图像融合方法</span></div><div class="t m0 x4 h5 y6 ff1 fs2 fc0 sc1 ls0 ws0">直接对源图像的各对应像素分别进行选择、平均或加权平均、多元回归或其</div><div class="t m0 x4 h5 y7 ff1 fs2 fc0 sc1 ls0 ws0">它数学运算等处理后,最终合成一幅融合图像。</div><div class="t m0 x2 h5 y8 ff3 fs2 fc0 sc1 ls0 ws0">(2)<span class="_ _0"></span><span class="ff1">基于<span class="_ _1"> </span></span>PCA<span class="_ _1"> </span><span class="ff1">的图像融合</span></div><div class="t m0 x4 h5 y9 ff1 fs2 fc0 sc1 ls0 ws0">又称<span class="_ _1"> </span><span class="ff3">K<span class="_ _2"></span>-L<span class="_ _1"> </span><span class="ff1">变换法,<span class="_ _3"></span>几何意义是把<span class="_ _3"></span>原始特征空间的特<span class="_ _3"></span>征轴旋转得到<span class="_ _3"></span>新的特征轴<span class="_ _4"> </span>,</span></span></div><div class="t m0 x4 h5 ya ff1 fs2 fc0 sc1 ls0 ws0">实际操作是将原来的各个因素指标重新组合,组合后的新指标是互不相关的<span class="_ _5"></span>。</div><div class="t m0 x4 h5 yb ff1 fs2 fc0 sc1 ls0 ws0">在由这些新指标组成的新特征轴中,只用前几个分量图像就能完全表征原始</div><div class="t m0 x4 h5 yc ff1 fs2 fc0 sc1 ls0 ws0">图像的有效信息。图像中彼此相关的数据被压缩,而特征得到了突出。</div><div class="t m0 x2 h5 yd ff3 fs2 fc0 sc1 ls0 ws0">(3)<span class="_ _0"></span><span class="ff1">基于<span class="_ _1"> </span></span>HIS<span class="_ _1"> </span><span class="ff1">变换的图像融合</span></div><div class="t m0 x4 h5 ye ff3 fs2 fc0 sc1 ls0 ws0">RGB<span class="_ _6"> </span><span class="ff1">颜色<span class="_ _3"></span>空<span class="_ _3"></span>间<span class="_ _3"></span>和<span class="_ _6"> </span></span>HIS<span class="_ _6"> </span><span class="ff1">色度<span class="_ _7"></span>空间<span class="_ _3"></span>有<span class="_ _3"></span>精<span class="_ _3"></span>确<span class="_ _3"></span>的<span class="_ _3"></span>转<span class="_ _3"></span>换<span class="_ _3"></span>关<span class="_ _3"></span>系<span class="_ _3"></span>。一<span class="_ _3"></span>般<span class="_ _3"></span>的<span class="_ _8"> </span></span>HIS<span class="_ _6"> </span><span class="ff1">图像<span class="_ _3"></span>融<span class="_ _3"></span>合<span class="_ _3"></span>方</span></div><div class="t m0 x4 h5 yf ff1 fs2 fc0 sc1 ls0 ws0">法是<span class="_ _3"></span>,<span class="_ _3"></span>先将<span class="_ _3"></span>被<span class="_ _3"></span>融<span class="_ _3"></span>合图<span class="_ _3"></span>像<span class="_ _3"></span>作<span class="_ _6"> </span><span class="ff3">RG<span class="_ _3"></span>B-HIS<span class="_ _1"> </span></span>变<span class="_ _3"></span>换<span class="_ _3"></span>,<span class="_ _3"></span>然后<span class="_ _3"></span>用<span class="_ _3"></span>一个<span class="_ _3"></span>较<span class="_ _3"></span>高<span class="_ _3"></span>空间<span class="_ _3"></span>分<span class="_ _3"></span>辨<span class="_ _3"></span>的灰<span class="_ _3"></span>度</div><div class="t m0 x4 h5 y10 ff1 fs2 fc0 sc1 ls0 ws0">图像<span class="_ _3"></span>的<span class="_ _3"></span>强度<span class="_ _3"></span>成<span class="_ _3"></span>分<span class="_ _3"></span>替换<span class="_ _3"></span>低<span class="_ _3"></span>分<span class="_ _3"></span>辨强<span class="_ _3"></span>度<span class="_ _3"></span>成分<span class="_ _3"></span>,<span class="_ _3"></span>然<span class="_ _3"></span>后再<span class="_ _3"></span>进<span class="_ _3"></span>行<span class="_ _8"> </span><span class="ff3">HI<span class="_ _3"></span>S-RGB<span class="_ _1"> </span></span>变<span class="_ _3"></span>换<span class="_ _3"></span>,<span class="_ _3"></span>得到<span class="_ _3"></span>融</div><div class="t m0 x4 h5 y11 ff1 fs2 fc0 sc1 ls0 ws0">合图像。</div><div class="t m0 x2 h5 y12 ff3 fs2 fc0 sc1 ls0 ws0">(4)<span class="_ _0"></span><span class="ff1">金字塔图像融合算法</span></div><div class="t m0 x4 h5 y13 ff1 fs2 fc0 sc1 ls0 ws0">金字塔图像融合法就是将参加融合的每幅源图像作金字塔表示,将所有图像</div><div class="t m0 x4 h5 y14 ff1 fs2 fc0 sc1 ls0 ws0">的金字塔表示在各相应层上以一定的融合规则融合,可得到合成的金字塔。</div><div class="t m0 x4 h5 y15 ff1 fs2 fc0 sc1 ls0 ws0">将合成的金字塔,用金字塔生成的逆过程重构图像,则可得到融合图像。</div></div></div><div class="pi" data-data='{"ctm":[1.611850,0.000000,0.000000,1.611850,0.000000,0.000000]}'></div></div>
</body>
</html>