cv2学习笔记6（色彩直方图）.ipynb

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    "# cv2学习笔记6\n",
    "## 色彩直方图\n",
    "### 绘制色彩直方图\n",
    "cv2.calcHistcv2.calcHist(images, channels, mask, histSize, ranges[, hist[, accumulate ]]) \n",
    "- 第一个参数必须用方括号括起来。\n",
    "- 第二个参数是用于计算直方图的通道，这里使用灰度图计算直方图，所以就直接使用第一个通道0\n",
    "- 第三个参数是Mask，这里没有使用，所以用None。\n",
    "- 第四个参数是histSize，表示这个直方图分成多少份（即多少个直方柱）。\n",
    "- 第五个参数是表示直方图中各个像素的值，[0.0, 256.0]表示直方图能表示像素值从0.0到256的像素。\n",
    "- 最后是两个可选参数，由于直方图作为函数结果返回了，所以第六个hist就没有意义了（待确定）\n",
    "- 最后一个accumulate是一个布尔值，用来表示直方图是否叠加。"
   ]
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   "source": [
    "import cv2      \n",
    "import numpy as np      \n",
    "      \n",
    "img = cv2.imread(\"C:/Users/situ.st.1/Pictures/splitman.jpg\")      \n",
    "b, g, r = cv2.split(img)   \n",
    "\n",
    "   #封装成一个函数                 \n",
    "def calcAndDrawHist(image, color):    \n",
    "    hist= cv2.calcHist([image], [0], None, [256], [0.0,255.0])\n",
    "    minVal, maxVal, minLoc, maxLoc = cv2.minMaxLoc(hist)    \n",
    "    histImg = np.zeros([256,256,3], np.uint8)    \n",
    "    hpt = int(0.9* 256);    \n",
    "        \n",
    "    for h in range(256):    \n",
    "        intensity = int(hist[h]*hpt/maxVal)    \n",
    "        cv2.line(histImg,(h,256), (h,256-intensity), color)    \n",
    "            \n",
    "    return histImg;   \n",
    "\n",
    "if __name__ == '__main__':    #主函数\n",
    "    img = cv2.imread(\"C:/Users/situ.st.1/Pictures/splitman.jpg\")    \n",
    "    b, g, r = cv2.split(img)    \n",
    "    \n",
    "    histImgB = calcAndDrawHist(b, [255, 0, 0])    \n",
    "    histImgG = calcAndDrawHist(g, [0, 255, 0])    \n",
    "    histImgR = calcAndDrawHist(r, [0, 0, 255])    \n",
    "        \n",
    "    cv2.imshow(\"histImgB\", histImgB)    \n",
    "    cv2.imshow(\"histImgG\", histImgG)    \n",
    "    cv2.imshow(\"histImgR\", histImgR)    \n",
    "    cv2.imshow(\"Img\", img)    \n",
    "    cv2.waitKey(0)    \n",
    "    cv2.destroyAllWindows()   "
   ]
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    "- 同时绘制三个通道的直方图\n"
   ]
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   "source": [
    "img = cv2.imread(\"C:/Users/situ.st.1/Pictures/splitman.jpg\") \n",
    "h = np.zeros((256,256,3)) #创建用于绘制直方图的全0图像    \n",
    "         \n",
    "bins = np.arange(256).reshape(256,1) #直方图中各bin的顶点位置    \n",
    "color = [ (255,0,0),(0,255,0),(0,0,255) ] #BGR三种颜色   \n",
    " \n",
    "for ch, col in enumerate(color):    #for循环是对三个通道遍历一次，每次绘制相应通道的直方图的折线！\n",
    "    originHist = cv2.calcHist([img],[ch],None,[256],[0,256])    \n",
    "    cv2.normalize(originHist, originHist,0,255*0.9,cv2.NORM_MINMAX) #归一化函数。该函数将直方图的范围限定在0-255×0.9之间\n",
    "    hist=np.int32(np.around(originHist))   #先将生成的原始直方图中的每个元素四舍六入五凑偶取整\n",
    "    pts = np.column_stack((bins,hist))     #将直方图中每个bin的值转成相应的坐标\n",
    "    cv2.polylines(h,[pts],False,col) #根据这些点绘制出折线，第三个False参数指出这个折线不需要闭合。第四个参数指定了折线的颜色。\n",
    "h=np.flipud(h)    #反转绘制好的直方图\n",
    "         \n",
    "cv2.imshow('colorhist',h)    \n",
    "cv2.waitKey(0)   "
   ]
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    "### 直方图均方化（增强对比度）\n",
    "在图像处理中，直方图均衡化一般用来均衡图像的强度，或增加图像的对比度。在介绍使用直方图均衡化来拉伸图像的直方图之前，先介绍使用查询表的方法。\n",
    "观察上图中原始图像的直方图，很容易发现大部分强度值范围都没有用到。因此先检测图像非0的最低（imin）强度值和最高（imax）强度值。\n",
    "将最低值imin设为0，最高值imax设为255。中间的按255.0*(i-imin)/(imax-imin)+0.5)的形式设置。"
   ]
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   "source": [
    "image = cv2.imread(\"C:/Users/situ.st.1/Pictures/caoyuan.jpg\", 0) \n",
    "cv2.imshow(\"origin\",image); \n",
    "lut = np.zeros(256, dtype = image.dtype )#创建空的查找表  \n",
    "hist= cv2.calcHist([image],[0],None,[256], [0.0,255.0])  \n",
    "      \n",
    "minBinNo, maxBinNo = 0, 255  \n",
    "#计算从左起第一个不为0的直方图位置  \n",
    "for binNo, binValue in enumerate(hist):  \n",
    "    if binValue != 0:  \n",
    "        minBinNo = binNo  \n",
    "        break  \n",
    "#计算从右起第一个不为0的直方图位置  \n",
    "for binNo, binValue in enumerate(reversed(hist)):  \n",
    "    if binValue != 0:  \n",
    "        maxBinNo = 255-binNo  \n",
    "        break  \n",
    "#print minBinNo, maxBinNo  \n",
    "  \n",
    "#生成查找表，方法来自参考文献1第四章第2节  \n",
    "for i,v in enumerate(lut):  \n",
    "    print i  \n",
    "    if i < minBinNo:  \n",
    "        lut[i] = 0  \n",
    "    elif i > maxBinNo:  \n",
    "        lut[i] = 255  \n",
    "    else:  \n",
    "        lut[i] = int(255.0*(i-minBinNo)/(maxBinNo-minBinNo)+0.5)  \n",
    "\n",
    "#计算  \n",
    "result = cv2.LUT(image, lut)  \n",
    "cv2.imshow(\"Result\", result)  \n",
    "cv2.waitKey(0)  \n",
    "cv2.destroyAllWindows()  \n",
    "\n",
    "#直方图均衡化之OpenCV函数实现\n",
    "img = cv2.imread('C:/Users/situ.st.1/Pictures/caoyuan.jpg',0)  \n",
    "equ = cv2.equalizeHist(img)  \n",
    "cv2.imshow('equ',equ)  \n",
    "cv2.waitKey(0)  \n",
    "cv2.destroyAllWindows() "
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