{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7.1 图像平面特征分类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.1.1 基于像元的图像分类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "像元分类现象：分类结果存在明显的椒盐现象。\n",
    "\n",
    "存在问题：不能区分同谱异物、难以分类异谱同物的像元。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](IMG71/Image711.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## 7.1.2 图像模式分类\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](IMG71/Image712.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "图像分类是建立输入图像和输出语义图之间可靠的映射关系。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](IMG71/Image713.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "图像平面空间关系建模（减少不必要的相互影响）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](IMG71/Image714.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7.2 实验要求"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "（1）理解基于像元的图像分类和图像模式分类的差异，相互之间的关系。\n",
    "\n",
    "（2）利用jupyter notebook实现基于最大似然分类法对影像进行分类。\n",
    "\n",
    "（3）实现空间升维、光谱升维对影像分类，比较结果精度差异，分析原因。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7.3 思考探索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "（1）图像分类的基本过程？ 思考图像模式分类的实质？\n",
    "\n",
    "（2）图像平面空间与特征空间的联系和转换？\n",
    "\n",
    "（3）空间上升维或者光谱上升维是否一定能够提高分类精度？ "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  },
  "toc": {
   "colors": {
    "hover_highlight": "#DAA520",
    "navigate_num": "#000000",
    "navigate_text": "#333333",
    "running_highlight": "#FF0000",
    "selected_highlight": "#FFD700",
    "sidebar_border": "#EEEEEE",
    "wrapper_background": "#FFFFFF"
   },
   "moveMenuLeft": true,
   "nav_menu": {
    "height": "30px",
    "width": "252px"
   },
   "navigate_menu": true,
   "number_sections": true,
   "sideBar": true,
   "threshold": 4,
   "toc_cell": false,
   "toc_position": {
    "height": "530px",
    "left": "0px",
    "right": "1108px",
    "top": "106px",
    "width": "252px"
   },
   "toc_section_display": "block",
   "toc_window_display": true,
   "widenNotebook": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}