ImageProcessing/lab1/DE_IP_2024_Task_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5d62d24",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2799ab25",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Базовая работа с изображением"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5037aa29",
   "metadata": {},
   "outputs": [],
   "source": [
    "image = cv2.imread('sar_2_color.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e5f356b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad6776dc40>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "37b8f016",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(572, 974, 3)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image.shape # h,w,c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e4530952",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([12, 12, 12], dtype=uint8)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image[250,250] # b,g,r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "51aab9ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ROI\n",
    "img_roi = image[100:200, 500:700]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "70010d8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad673c1e80>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(img_roi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f882dac3",
   "metadata": {},
   "outputs": [],
   "source": [
    "b,g,r = cv2.split(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1f89e4b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad673bd160>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(b, cmap = 'gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80f48335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad66fc5a60>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAFUCAYAAAAOBceiAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzsvVlwZNl1HbpyQM4Dcs7EPBdQ89zd1c3uaqpJkRJJUZRkyrQkW/6wZIUdoZAjbCv8YzkcobA//OFw2A792LIUEimGTFEUxSZ7nrvmKlShMA+JBDITiZznOd8HtHYdXKLp9rP9yH7GiagoIJF58+bNe85Ze+2119b1er0ejsfxOB7H43gcj+NxPH6Chv7HfQLH43gcj+NxPI7H8Tge2nEMUI7H8Tgex+N4HI/j8RM3jgHK8Tgex+N4HI/jcTx+4sYxQDkex+N4HI/jcTyOx0/cOAYox+N4HI/jcTyOx/H4iRvHAOV4HI/jcTyOx/E4Hj9x4xigHI/jcTyOx/E4HsfjJ24cA5TjcTyOx/E4HsfjePzEjWOAcjyOx/E4HsfjeByPn7hxDFCOx/E4HsfjeByP4/ETN36sAOU//sf/iPHxcVgsFly6dAnvvPPOj/N0jsfxOB7H43gcj+PxEzJ+bADlG9/4Bn77t38b/+Jf/Avcu3cPn/rUp/D5z38e29vbP65TOh7H43gcj+NxPI7HT8jQ/biaBT711FO4ePEi/tN/+k/y2NzcHL785S/j93//938cp3Q8jsfxOB7H43gcj5+QYfxxvGmz2cSdO3fwz//5Pz/0+Gc/+1m8//77P/T8RqOBRqMhv3e7XWSzWfh8Puh0uv/j53s8jsfxOB7H43gcj//10ev1UCqVMDAwAL3+RydxfiwAJZ1Oo9PpIBQKHXo8FAohmUz+0PN///d/H7/3e7/3/9XpHY/jcTyOx/E4Hsfj/+CIxWIYGhr6kc/5sQAUDi370ev1jmREfvd3fxe/8zu/I78XCgWMjIxgamoK3W4XXq8XDocDBoMBU1NTiMViyOVyaLfbCAQCMJlMsNvtsFqtWFpagsPhgNFoRLFYhNPpRLvdRqVSQTgcRiqVgsFgQLFYhMlkQq/XQ19fH/R6PXw+H7rdLlwuF0qlEvr6+pBMJqHX6xGJRJDP59FoNGC1WlEul2Gz2aDX66HT6TA4OIhSqQQAqFarmJ2dhcfjwa1bt7C/vw+n04lgMIidnR24XC5UKhXodDr4fD4Ui0WYzWbkcjkAgF6vR7fbhdFoxPDwMHQ6HXK5HCqVCsxmM3w+HxqNBkqlEiqVCqrVKtxuN0ZGRtDtdrG/v4/+/n7k83ns7OxgYmIC3W4X6XQamUwGRqMRXq8XhUIB6XQaBoMBRqMRg4ODsNlsiMViaDQaMJlMaLfbsNlscj35mSuVCoxGIwwGA0wmE9xuN8xmM2w2m3zWfD6PYrEIg8EAvV6PWq2GbDaLZDKJTqcDnU6HarWKTqeDbreLQqEAg8EAq9WKbreLSqUCl8uFRqOBXq+HbrcLm82Gvr4+uN1u7O7uIpPJoNfrQc1k6nQ6udd4Ld1uN55++mns7u6iVCqh3W5jaGgINpsNiURCrmM+n0en0xHkrx632+3K8XU6HQwGA3q9HvR6/aF7W/uz+hp+v51O59Bx1eN1u105Lq8TAJhMJly8eBF9fX2o1+soFAqoVCqYmZlBf38/1tbWUC6XMTAwgM3NTTmvaDR66NpEIhFYLBZUKhW43W6Uy2WEw2FsbGygWq3CaDSir68PAITF9Hq92Nvbw9jYGEKhEOLxOEKhEFqtFgDA6/XC6XSi2+3i/PnzqFQq+O53v4tAIACLxSJzOhAIoFKp4MGDB4jFYuh0OrBarfD5fNjZ2UGr1YLFYsHU1BQGBgbkful2u4hEIggEAuj1enj06BF6vR6KxSLq9ToajQYMBgP6+vowMjKC/v5++P1+7OzsoFarybx59OgRTCYT+vr6YLfbsbCwgFAohEKhgEajgXK5LPek1+tFq9WS+y2VSqHT6cDlckGv16NarSIUCkGn06FcLsPlcsFoNMJqtaJer6Pb7aLT6SCVSqFer8NgMKBQKMBisWB8fByZTAbVahXBYBC1Wk3WhF6vB6vVCofDgVKphG63i3q9DrvdDgAS/FUqFZmLer0ebrcber0e5XIZ3W4XZrMZADAzM4O9vT2Ew2FkMhlZoxqNBoxGo6xp/f398Hg8GBgYQLlchk6ng9vthsfjwcbGBnQ6HZLJJK5fvy6Pra6uwufzIZvNYmBgAJ1OB7u7u6hUKtjf35fv0263w263o9PpoFqtol6vo91uo6+vD+FwGM1mU97b6XRK9D06Ogqn04lCoYCNjQ3cuHED9XodX/3qVzE4OIhoNIpsNotHjx5hYGAAZ86cwfLyMjKZDC5evCjrc6FQwM7ODu7fv48TJ07g2WefRV9fH1ZWVlAul2U9e+utt/DSSy8hnU7LNf3ud7+LRCKBixcv4h/9o3+EbreLxcVF/OVf/iVcLhfsdju2t7cxPz8Pj8eD0dFRmRMAcPXqVaTTady/fx+5XA5WqxX5fB4mkwnhcBi/+Zu/Cb/fj1QqhXK5jLt37+L999+HxWLBc889B5PJhOHhYczPz+Px48eoVCqwWq3Y3d3Fl770JdTrddmPBgcHkUqlkEgkMD09jUgkgu3tbRQKBQwMDKBQKCAajWJ+fh7JZBI+nw8nT55EPp+HXq9HvV5HrVbDyZMncenSJTx+/BivvvoqqtUqvF4vxsfHUavV4Pf70Ww2YTabceLECRiNRjx8+BDVahV7e3u4ffs2nE7nkbhAHT8WgOL3+2EwGH6ILUmlUj/EqgCA2WyWyaQOvV4vG7fJZEKz2cTS0hLC4TD0er0spPyfi7rb7cbe3h46nQ6y2SzMZjOcTidyuZwswCaTCT6fD7lcDp1OB319fQgGg/D5fOjr68P29jZsNhtsNhtyuRyGh4cxNTWFaDSKcrmMZrMJvV4Pi8UCh8MBh8Mhi1QwGEQmk5HNORKJoFKpoFgsAoCcQygUQiaTQavVgtVqhdFoRLPZRK1WQ6/Xg8fjwe7uLgqFAoLBIPR6PVqtFjY3NwFAbvBUKiXAq7+/H9VqFTabDQaDARMTE8jn89DpdKjX6xgYGEC73Ua324XVakUgEECpVILVapWFyuVyyblarVYYDAaMjIwglUqh2WwCAGw2G0wmE+r1Omw2G9rtNgwGA5xOJ0wmEyqVirzXzs4OFhcXYbVa5Vp3u12kUilYrVbUajVZHBuNBvR6PfR6PRwOh2xgvV4PNpsN2WwWbrdbQBXwBBBogQmBi8FgQK1Ww+3bt3H69GlZBLkwBQIBlMtltFotdLvdQ7SkCj4IdgwGAwAceoz/c/B9jwIo2sfUY6rghKCFo9Vq4d69exgcHESz2cTOzg663S52d3dhNBrltVtbW9DpdAKCeJ4E2nq9HtlsFkajEbu7u7Db7Wi1WqhWq+h2u+h2u2i32zCbzahUKiiVSsjn8+h2u/jwww8RCoUwOjqKarUKk8kEs9mMVquFZrOJyclJmZtPPfUUTCYT7t+/D6vVKve5w+HA6Ogo2u02yuWynKPf70exWJTrX6vVYLPZEAgEUK1W0Ww2kUwmUa/Xsbe3B5/Ph9nZWQDA9vY24vG4fLZyuYxkMgmv14t2u41OpyPgKpPJyNweHR1FPB6H1+uVczEajajVajCZTDAYDKjX6zAajYhEItjd3ZVNNhKJwOPxwOv1yjzIZrPI5/Myl3U6HSwWC3Q6HRwOB1wul1xLrh2cAw6HA/V6XTbLfD4Pu92OZrMJk8kE4CAdzuvdarVgMBjkvrJarQiHwwLejEYjKpUK2u02fD6fbOD3799HtVqV47jdbjQaDTgcDtjtdrmfjEYjzp49K+tnNBqFx+PB5uYmRkdHcfbsWQEj4+PjCIfDKBQK8Hg82N7ehl6vF3DG+Vyv15HJZBAIBNDpdOQ6BYNBmEwmlMtlNBoNDA8Pw+/3w+12o1KpAADu3buHvb09XLlyBcFgEMViEc1mE9FoFDs7O2g0GpiZmZHrzPszEAggm81iY2MDly5dQj6fR7l
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(g, cmap = 'gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "14bf6bec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# alternative approach\n",
    "b = image[:,:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "65f6cb65",
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "\n",
    "image2 = copy.deepcopy(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6e348740",
   "metadata": {},
   "outputs": [],
   "source": [
    "image2[50:100,50:100] = [0,0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f0af9079",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad5cd46150>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7b3beafd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# empty image\n",
    "image_template = np.zeros(image.shape,np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "649438f3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad673d2960>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image_template)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c9b56ab",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Конвертация цветовых моделей"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ddf46c8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0], dtype=uint8)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_template[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "90601bc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4254803d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.uint8(40)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_gray[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "abb0a164",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(572, 974)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_gray.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f282c88e",
   "metadata": {},
   "outputs": [],
   "source": [
    "image_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d37c08b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(572, 974, 3)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_hsv.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ae9ef2ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([117, 143,  75], dtype=uint8)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_hsv[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d8cdda21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([75, 37, 33], dtype=uint8)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "73fdb374",
   "metadata": {},
   "outputs": [],
   "source": [
    "image_lab = cv2.cvtColor(image, cv2.COLOR_BGR2Lab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0ed9c8e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 42, 139, 104], dtype=uint8)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_lab[0,0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0d7f4f0",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Пороговая фильтрация"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0b6d5e3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "_,thresh1 = cv2.threshold(image_gray,200,255,cv2.THRESH_BINARY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6e84b905",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad5cda2360>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(thresh1, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f5e1453e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.uint64(0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "thresh1[thresh1==100].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "396e3b66",
   "metadata": {},
   "source": [
    "## Построение гистограммы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4b455e07",
   "metadata": {},
   "outputs": [],
   "source": [
    "histSize = 256\n",
    "histRange = (0, 256)\n",
    "accumulate = False\n",
    "\n",
    "b_hist = cv2.calcHist([b], [0], None, [histSize], histRange, accumulate=accumulate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "477df536",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fad66fb35c0>]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(b_hist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "92636df5",
   "metadata": {},
   "outputs": [],
   "source": [
    "b_hist_cum = b_hist.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1a195130",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fad5cb2c860>]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkIAAAGdCAYAAAD+JxxnAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAASRhJREFUeJzt3XlcVPe5P/APAzPDiDCCCMMIKsa4BSQRFTWJGK0mVjRp0jZRQzSLrUkw9cbeJja3V683v+BNrb23GpNmMWarpK2aNomlamI0VhAEUXCLxoVFEEWYYZ31+f2BTjKuoMCZ5fN+veYFzHmYec43I+eTc77nnAARERARERH5IZXSDRAREREphUGIiIiI/BaDEBEREfktBiEiIiLyWwxCRERE5LcYhIiIiMhvMQgRERGR32IQIiIiIr8VpHQDns7pdOL06dMIDQ1FQECA0u0QERFRG4gI6uvrYTQaoVJdfb8Pg9B1nD59GnFxcUq3QURERDegrKwMsbGxV13OIHQdoaGhAFoHMiwsTOFuiIiIqC3MZjPi4uJc2/GrYRC6jouHw8LCwhiEiIiIvMz1prVwsjQRERH5LQYhIiIi8lsMQkREROS3GISIiIjIbzEIERERkd9iECIiIiK/xSBEREREfotBiIiIiPwWgxARERH5LQYhIiIi8lsMQkREROS3GISIiIjIb/Gmq0RERHRdTqfAYneixeZAi92BFtuF722t31vsDtgdApvDCZtTYHc4W793tH5vdwqsDifsF362OQU2e+vzPxgSjbtujVRkvRiEiIiIfJDDKWhoscPcYkP9977WX/y52YZ6S+vP5hY7GlrsaLY5YLkQbFrDzneBx2J3dlqvUWFaBiEiIiJy53QKzC021DRacb7RipqG1q91zVaYm78LNRfDzHc/29FgsXdaX0GqAASrAxGsVl34GghtkApBgSpoAgMQpFIhKDAA6kAV1IEBCApUQa1q/Tno4nMqFdRBAVCrVEjuE95pvV53XRR7ZyIiIj9ldzhxrsGKM+aW1ke9BWfNLThjtuBMfevXs/UW1DZZ4XDKTb2XNkiF0GA1wnRBrV+DgxAaHIRQ7XfPhQYHobs2CDpNIIKDAi8LOW7fXwg8voJBiIiIqAPZHU5UmlpQdr4JZbVNqDS1Bptqc4sr5JxrsEDakW9CtUGI6K5BRIgGPUM06NFNg7ALASY0OAhhwe6h5rvAo4YmyHdCS2dgECIiImoHEUFtkw1l55tQeuFRXtv6tex8M07XNcPehr04gaoA9OquRXSYFlFhwa1fQ4NdP/fqrkXPC+FHGxTYBWvmnxiEiIiIrqDJasex6gYcqarH0eoGnDzXeCH0NF93/o0mUIXYcB3iIrrB2CMY0WEXH61hJypMi54hWgSqArpobehqGISIiMivWe1OHD/XGni+OVOPI1UN+OZMPcpqm655+Co6TIs+Ed0QF94NcRGtjz4R3RAXoUN0aDBUDDlegUGIiIj8Rk2DBfvLTSiuMOHImXp8U1WPE+car3ooK7K7BgOjQzEwOhT9e4W0Bp7wbogN1yFYzcNVvoBBiIiIfFKT1Y4Dp83YV1aHorI67CuvQ9n55ivWhgYHYVB0KAYaQlu/RodiYHR39Oyu7eKuqasxCBERkdezO5w4Wt2AfRcCT1GZCd+cqb/iqee39ApBUmwPDI5pDTyDDKEwhAUjIICHsvwRgxAREXmduiYrco+fR8Gp89hX1nqoq9nmuKwuKlSL2+N6ICmuB26P64HEWD3CgtUKdEyeikGIiIg8nrnFht3HzyPn2xrkHK/B4SrzZROZu2uDMCxWj6S4HkiKbQ0+Bn2wMg2T12AQIiIijyMiOFbdgC8PV+PLw9XYc6r2ssNcA6K6IyU+Anf0CcftcXr0j+zOM7Wo3RiEiIjII7TYHMg9XoNth6vx5ZHqyyY2x0eGYMwtPTG6f0+M7h+BqFDu7aGbxyBERESKqTK1uPb6/OvYObd5PppAFUbf0hMTBvXChMHR6NOzm4Kdkq9iECIioi7jcAqKyuqw7XA1vjhcjUOVZrfl0WFaTBgchQmDo3HngJ7opuFmijoXP2FERNSpWmwOfHm4GlsPnsFX35zF+Uara1lAAHB7XA9MHByFewZHYWhMGE9jpy7FIERERB3O5nBi59Fz+Pu+09h8oAqN1u8OeYUGByF1YC9MGByF1IG9eNFCUhSDEBERdQiHU7D7RA0+3VeJf5RUoq7J5lrWu4cOU4fFYMLgKCT3DYc6UKVgp0TfYRAiIqIbJtI65+fTfZX4bP9pVNdbXMsiu2uRNiwG05KMGN6nBw95kUdiECIionY7XGXG34tO49P9p91Oc9fr1JiSYMC0JCNG9++JQF7XhzwcgxAREbVJpakZGwor8LeiCnxzpsH1fDdNICYNjca0YUaMG9gLmiAe9iLvwSBERERXZbE7sOXgGfx5Tzm+PnrWdVsLTaAK4wf1wrQkIyYOieJp7uS1+MklIqLLHK4yIyuvDJ8UVbhNek6Jj8BDybG49zYD9DrevJS8H4MQEREBaL3ez+f7K/GnvFIUnKp1PR+jD8ZDw2Px4+RY9IsMUbBDoo7HIERE5OeOVTdgXV4p/lpQDlNz696fQFUAJg2JxoyUPrhrQCQnPZPPYhAiIvJDDqdgy8EqrN11ErnHz7ue791Dhxmj4vDTEXGICuNNTcn3MQgREfmR+hYb/rynHGt3nXCd9q4KACYMjsaslD4YN7AX9/6QX2EQIiLyA2Xnm/Duv07iz3vK0GCxAwDCu6kxK6UvZqb0gbGHTuEOiZTBIERE5MOKyurwx+3f4p8HquC8cOr7gKjueOLOePzojt7QaQKVbZBIYQxCREQ+KP/kefzhi6P4+ug513N33xqJJ++Kx7hbe0HFw19EAIB2Xf5zyZIlCAgIcHsYDAbXchHBkiVLYDQaodPpMH78eBw4cMDtNSwWC+bPn4/IyEiEhIRg+vTpKC8vd6upra1Feno69Ho99Ho90tPTUVdX51ZTWlqKadOmISQkBJGRkXjuuedgtVrdaoqLi5GamgqdTofevXtj6dKlkItXAyMi8jEigl3fnsMjb+bgJ2/k4Ouj5xCoCsCDw3vjnwvG4YMnUzB+UBRDENH3tHuP0G233YatW7e6fg4M/G636quvvooVK1Zg7dq1GDhwIF5++WVMmjQJR44cQWhoKABgwYIF+PTTT5GVlYWePXti4cKFSEtLQ0FBgeu1Zs6cifLycmRnZwMAfvaznyE9PR2ffvopAMDhcGDq1Kno1asXdu7ciZqaGsyePRsigpUrVwIAzGYzJk2ahHvuuQf5+fn45ptvMGfOHISEhGDhwoU3OFxERJ5HRLDj6Dms/OIo9ly4/o86MAA/To7F06kD0KdnN4U7JPJg0g6LFy+WpKSkKy5zOp1iMBhk2bJlrudaWlpEr9fLG2+8ISIidXV1olarJSsry1VTUVEhKpVKsrOzRUTk4MGDAkByc3NdNTk5OQJADh8+LCIimzZtEpVKJRUVFa6adevWiVarFZPJJCIiq1evFr1eLy0tLa6azMxMMRqN4nQ627zOJpNJALhel4jIUzidTtlyoEqmr/xa+r7wmfR94TO59aVN8ptPiqW8tknp9ogU1dbtd7vvjHf06FEYjUbEx8fjkUcewfHjxwEAJ06cQFVVFSZPnuyq1Wq1SE1Nxa5duwAABQUFsNlsbjVGoxEJCQmumpycHOj1eqSkpLhqRo8eDb1e71aTkJAAo9Hoqrn33nthsVhQUFDgqklNTYVWq3WrOX36NE6ePNne1SYi8hgiguySSkz9w0489f4e7Cs3IVitwhN3xuPrX92DpfcnoDfPAiNqk3YdGktJScH777+PgQMH4syZM3j55ZcxduxYHDhwAFVVVQCA6Ohot9+Jjo7GqVOnAABVVVXQaDQIDw+/rObi71dVVSEqKuqy946KinKrufR9wsPDodFo3Gr69et32ftcXBYfH3/FdbRYLLBYLK6fzWbz1QeEiKgLyYVDYMv/eQTFFSYArXd+Tx/TF3Pv7o/I7trrvAIRXapdQWjKlCmu7xMTEzFmzBjccssteO+99zB69Gg
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(b_hist_cum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e11f8476",
   "metadata": {},
   "outputs": [],
   "source": [
    "b_hist_norm = b_hist /  (image.shape[0] * image.shape[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ae7a2b79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fad5cb916d0>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(b_hist_norm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa3739f4",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Сравнение двух изображений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b67e4981",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SSIM: 1.0\n"
     ]
    }
   ],
   "source": [
    "from skimage.metrics import structural_similarity, mean_squared_error\n",
    "\n",
    "(ssim, diff) = structural_similarity(image_gray, image_gray, full=True)\n",
    "diff = (diff * 255).astype(\"uint8\")\n",
    "print(\"SSIM: {}\".format(ssim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e130dabe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad42eeb890>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(diff)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "03ab140b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.0)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mse = mean_squared_error(image_gray, image_gray)\n",
    "mse"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7c085bc",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Статистические характеристики изображений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "de9202f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean = image_gray.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "aaff4206",
   "metadata": {},
   "outputs": [],
   "source": [
    "std = image_gray.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "248147b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "67.41225535245043 52.016191875959635\n"
     ]
    }
   ],
   "source": [
    "print(mean,std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3fbab27e",
   "metadata": {},
   "outputs": [],
   "source": [
    "eq_gray = cv2.equalizeHist(image_gray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "250af16c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad42f65160>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(eq_gray, cmap=\"gray\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "7c013a0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fad42f6ea50>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image_gray, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3ad3ea1-b103-4383-8219-946233ef84c5",
   "metadata": {},
   "source": [
    "# Задание"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "6329e214",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. Загрузите изображение в оттенках серого sar_1_gray.jpg. \n",
    "# 2. постройте гистограмму\n",
    "# 3. реализуйте алгоритм гамма коррекции с параметром гамма <1, >1.\n",
    "# 4. Сравните исходное изображение, скорректированное при помощи гамма-фильтра. MSE, SSIM.\n",
    "# 5. реализуйте алгоритм статистической цветокоррекции на основе статистики eq_gray.\n",
    "# 6. Протестируйте работу алгоритмов пороговой фильтрации с различными параметрами.\n",
    "# Для каждого решения - напечатайте результат\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "2427bbf1-ffed-4948-80e5-a102df665e9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#1\n",
    "image_gray = cv2.imread('sar_1_gray.jpg', cv2.IMREAD_GRAYSCALE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3134249-c6c5-4373-bcf1-09bee7f2a87d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.12.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}