OpenCV基础知识

色彩空间 RGB与BGR

• RGB：人眼的色彩空间
• OpenCV默认使用BGR

  

  RGB

  

  BGR

HSV与HSL

• HSV

  • Hue：色相，即色彩，如红色，蓝色
  • Saturation：饱和度，颜色的纯度
  • Value：明度

    

    HSV

    

    HSV

    

    HUE

• HSL

  • Hue：色相
  • Saturation：饱和度
  • Lightness：亮度

    

    HSL 与 HSV的区别

OpenCV为什么要使用HSV

OpenCV可以针对颜色的色相进行判断，RGB不好判断。

OpenCV色彩空间转换

• YUV 主要用在视频中，编解码器一般都会使用yvu作为数据源。对于yvu来说主要包括三种类型
  1. YUV4:2:0
  2. YUV4:2:2
  3. YUV4:4:4

注意

以上都是对于像素的描述，例如 YUV4:4:4 代表4个Y数据，4个U数据，4个V数据。Y代表灰色的录像，UV代表颜色。比如以前家用的黑白电视，黑白电视用的就是数据 Y，有了彩色电视，兼容黑白电视就有了YUV。这样彩色电视即可以播放黑白画面，也可以播放彩色画面。YUV4:4:4类似RGB，RGB是8:8:88个红色 8个绿色 8个蓝色。
YUV4:2:0 是一个标准，它比 YUV4:4:4 存储空间节省一半。我们的音视频编解码器都是以这个为标准的。

YUV4:2:0,在第一行4个Y里有2个U,第二行4个Y里有2个V没有U.

• OpenCV色彩空间转换支持的转换方式¹
• 范例

  import cv2
  
  def callback(userdata):
      pass
  
  cv2.namedWindow('color', cv2.WINDOW_NORMAL)
  
  img = cv2.imread('./RMB.jpeg')
  
  colorspaces = [cv2.COLOR_BGR2RGBA, cv2.COLOR_BGR2BGRA, 
              cv2.COLOR_BGR2GRAY, cv2.COLOR_BGR2HSV, 
              cv2.COLOR_BGR2YUV]
  cv2.createTrackbar('curcolor', 'color', 0, len(colorspaces), callback)
  
  while True:
      index = cv2.getTrackbarPos('curcolor', 'color')
  
      #颜色空间转换API
      cvt_img = cv2.cvtColor(img, colorspaces[index])
  
      cv2.imshow('color', cvt_img)
      key = cv2.waitKey(10)
      print(key)
      if key & 0xFF == ord('q'):
          break
  
  cv2.destroyAllWindows()
  

  

  色彩空间转换结果

Numpy基本操作

Numpy

OpenCV中用到的矩阵都需要转换成Numpy
Numpy是一个经高度优化的Python数值库

• 创建矩阵：图形的处理就是矩阵的处理
• 检索与赋值[y, x]：获取矩阵中某个元素的值，并且可以改变这个元素的值
• 获取子数组[:, :]：获取大的矩阵中的某一小块矩阵，或者给某一小块矩阵赋值

Numpy创建矩阵

• 创建数组
• 创建全0数组 zeros()/ones：全部是0 或 1
• 创建全值数组 full()：比如创建一个8x8的矩阵，矩阵中的值都是指定的值，比如100 每个元素都是100
• 创建单元数组 identity/eye()：简称为单元矩阵或单位矩阵，单位矩阵表示斜角都是1的 两边都是0的就叫单位矩阵，单位矩阵一般是正方形的(3x3 4x4 8x8等)，eye是非正方形的矩阵(3x5 9x20等)

array

• np.array([2, 3, 4])
• np.array([[1.0, 2.0],[3.0, 4.0]])

  import numpy as np
  # 通过array定义矩阵
  a = np.array([1, 2, 3])
  b = np.array([[1, 2, 3], [4, 5, 6]])
  print(a)
  print(b)
  
  '''
  输出
  [1 2 3]
  [[1 2 3]
  [4 5 6]]
  '''
  

zeros

• np.zeros((480, 640, 3), np.uint8)
  • (480, 640, 3): （行的个数 高度, 列的个数 宽度, 通道数/层数 n层）
  • np.uint8: 矩阵中的类型

    import numpy as np
    # 定义zeros矩阵
    c = np.zeros((3, 3, 3), np.uint8)
    print(c)
    
    '''
    输出
    [[[0 0 0]
    [0 0 0]
    [0 0 0]]
    [[0 0 0]
    [0 0 0]
    [0 0 0]]
    [[0 0 0]
    [0 0 0]
    [0 0 0]]]
    '''
    

ones

• 同zeros

  # 定义ones矩阵
  d = np.ones((4, 4), np.uint8)
  print(d)
  
  '''
  输出
  [[1 1 1 1]
  [1 1 1 1]
  [1 1 1 1]
  [1 1 1 1]]
  '''
  

full

• np.full((480, 640, 3), 255, np.uint8)

  • (480, 640, 3): （行的个数 高度, 列的个数 宽度, 通道数/层数 n层）
  • 255: 表示每个元素的数值
  • np.uint8: 矩阵中的类型

  # 定义full矩阵
  e = np.full((4, 4), 8, np.uint8)
  print(e)
  
  '''
  输出
  [[8 8 8 8]
  [8 8 8 8]
  [8 8 8 8]
  [8 8 8 8]]
  '''
  

  identity

  • np.identity(n): 斜对角是1, 其余是0
  • n 为 n x n 的矩阵

    # 定义单位矩阵
    f = np.identity(4)
    print(f)
    
    '''
    输出
    [[1. 0. 0. 0.]
    [0. 1. 0. 0.]
    [0. 0. 1. 0.]
    [0. 0. 0. 1.]]
    '''
    

  eye

  • np.eye((x, y), k=z)：可以是非正方形
  • x: 高
  • y: 宽
  • z: 斜对角偏移个数

    g = np.eye(3, 5, k=1)
    print(g)
    
    '''
    输出
    [[0. 1. 0. 0. 0.]
    [0. 0. 1. 0. 0.]
    [0. 0. 0. 1. 0.]]
    '''
    

Numpy - 矩阵的检索与赋值

• 矩阵检索与赋值

  • [y, x]
    • 通过下标检索，y在前面 x在后面
    • 检索矩阵的索引值从0开始，如比我们检索5,3 实际访问的却是6,4
  • [y, x, channel]
    • 对于RGB或BGR来说，一般是含有多通道的，所以在表示的时候就是 Y X 通道数/层数 (也可以认为成x y z)。

  img = np.zeros((480, 640, 3), np.uint8)
  #从矩阵中读某个元素的值
  print(img[100, 100])
  count = 0
  
  #向矩阵中某个元素赋值
  while count < 200:
      #BGR
      img[count, 100] = [255, 255, 255]
      count = count + 1
  
  cv2.imshow('img', img)
  key = cv2.waitKey(0)
  if key & 0xFF == ord('q'):
      cv2.destroyAllWindows()
  

  

  结果

  Numpy - ROI

• 获取子矩阵 ROI: Region of Image（图像中的某一块区域）

  • [[y1, y2],[x1, x2]]: 局部获取及变更
  • [:, :] : 所有图像获取及变更

  img = np.zeros((480, 640, 3), np.uint8)
  #从矩阵中读某个元素的值
  print(img[100, 100])
  count = 0
  
  #向矩阵中某个元素赋值
  while count < 200:
      #BGR
      img[count, 100] = [255, 255, 255]
      count = count + 1
  
  roi = img[100:400, 100:600]
  #roi[:,:] = [0,0,255]
  roi[:] = [0,0,255]
  roi[:,10] = [0, 0, 0]
  roi[10:200,10:200] = [0,255,0]
  
  cv2.imshow('img', roi)
  key = cv2.waitKey(0)
  if key & 0xFF == ord('q'):
  cv2.destroyAllWindows()
  

  

  结果

OpenCV的重要结构体Mat

• Mat是矩阵，如果是黑白色即只有1个通道，如果是彩色即有3个通道
• Mat的好处是使用Numpy直接可以用矩阵的方式进行访问，操作方便
  • Mat的结构
    • Header：存放了一些属性，属性包括 dims维数、rows行、cols列数、*data指针（存储数据的指针，头指向某一个data）、*refcount引用计数/修改（防止内存泄露，引用修改方式）。
    • Data：存储数据部分，图像的颜色

      

      Mat的大致结构

      

      Mat的属性

Mat的深拷贝与浅拷贝

import cv2

img = cv2.imread('./RMB.jpeg')

# 浅拷贝
img2 = img

# 深拷贝
img3 = img.copy()

img[100: 200, 100: 200] = [0, 0, 255]

cv2.imshow('img', img)
cv2.imshow('img2', img2)
cv2.imshow('img3', img3)

cv2.waitKey(0)

Mat的深拷贝与浅拷贝

图像的多种属性

• 访问图像mat的属性

  import cv2
  import numpy as np
  
  img = cv2.imread('RMB.jpeg')
  
  #shape属性中包括了三个信息
  #高度，长度 和 通道数
  print(img.shape)
  
  #图像占用多大空间
  #高度 * 长度 * 通道数
  print(img.size)
  
  #图像中每个元素的位深
  print(img.dtype)
  
  '''
  输出
  
  (4032, 3024, 3)
  36578304
  uint8   # 0~255
  '''
  

通道的分割与合并

• split(mat)
• merge((ch1, ch2, ...))

  import cv2
  import numpy as np
  
  img = np.zeros((480, 640, 3), np.uint8)
  
  b,g,r = cv2.split(img)
  
  b[10:100, 10:100] = 255
  g[10:100, 10:100] = 255
  
  img2 = cv2.merge((b, g, r))
  
  cv2.imshow('img', img)
  cv2.imshow('b', b)
  cv2.imshow('g', g)
  cv2.imshow('img2', img2)
  
  cv2.waitKey(0)
  

Mat的深拷贝与浅拷贝

扩展信息

• COLOR_BGRA2BGR = 1, //!< remove alpha channel from RGB or BGR image
  

• COLOR_RGBA2RGB = COLOR_BGRA2BGR,
  
  

• COLOR_BGR2RGBA = 2, //!< convert between RGB and BGR color spaces (with or without alpha channel)
  

• COLOR_RGB2BGRA = COLOR_BGR2RGBA,
  
  

• COLOR_RGBA2BGR = 3,
  

• COLOR_BGRA2RGB = COLOR_RGBA2BGR,
  
  

• COLOR_BGR2RGB = 4,
  

• COLOR_RGB2BGR = COLOR_BGR2RGB,
  
  

• COLOR_BGRA2RGBA = 5,
  

• COLOR_RGBA2BGRA = COLOR_BGRA2RGBA,
  
  

• COLOR_BGR2GRAY = 6, //!< convert between RGB/BGR and grayscale, @ref color_convert_rgb_gray "color conversions"
  

• COLOR_RGB2GRAY = 7,
  
• COLOR_GRAY2BGR = 8,
  
• COLOR_GRAY2RGB = COLOR_GRAY2BGR,
  
• COLOR_GRAY2BGRA = 9,
  
• COLOR_GRAY2RGBA = COLOR_GRAY2BGRA,
  
• COLOR_BGRA2GRAY = 10,
  

• COLOR_RGBA2GRAY = 11,
  
  

• COLOR_BGR2BGR565 = 12, //!< convert between RGB/BGR and BGR565 (16-bit images)
  

• COLOR_RGB2BGR565 = 13,
  
• COLOR_BGR5652BGR = 14,
  
• COLOR_BGR5652RGB = 15,
  
• COLOR_BGRA2BGR565 = 16,
  
• COLOR_RGBA2BGR565 = 17,
  
• COLOR_BGR5652BGRA = 18,
  

• COLOR_BGR5652RGBA = 19,
  
  

• COLOR_GRAY2BGR565 = 20, //!< convert between grayscale to BGR565 (16-bit images)
  

• COLOR_BGR5652GRAY = 21,
  
  

• COLOR_BGR2BGR555 = 22, //!< convert between RGB/BGR and BGR555 (16-bit images)
  

• COLOR_RGB2BGR555 = 23,
  
• COLOR_BGR5552BGR = 24,
  
• COLOR_BGR5552RGB = 25,
  
• COLOR_BGRA2BGR555 = 26,
  
• COLOR_RGBA2BGR555 = 27,
  
• COLOR_BGR5552BGRA = 28,
  

• COLOR_BGR5552RGBA = 29,
  
  

• COLOR_GRAY2BGR555 = 30, //!< convert between grayscale and BGR555 (16-bit images)
  

• COLOR_BGR5552GRAY = 31,
  
  

• COLOR_BGR2XYZ = 32, //!< convert RGB/BGR to CIE XYZ, @ref color_convert_rgb_xyz "color conversions"
  

• COLOR_RGB2XYZ = 33,
  
• COLOR_XYZ2BGR = 34,
  

• COLOR_XYZ2RGB = 35,
  
  

• COLOR_BGR2YCrCb = 36, //!< convert RGB/BGR to luma-chroma (aka YCC), @ref color_convert_rgb_ycrcb "color conversions"
  

• COLOR_RGB2YCrCb = 37,
  
• COLOR_YCrCb2BGR = 38,
  

• COLOR_YCrCb2RGB = 39,
  
  

• COLOR_BGR2HSV = 40, //!< convert RGB/BGR to HSV (hue saturation value) with H range 0..180 if 8 bit image, @ref color_convert_rgb_hsv "color conversions"
  

• COLOR_RGB2HSV = 41,
  
  

• COLOR_BGR2Lab = 44, //!< convert RGB/BGR to CIE Lab, @ref color_convert_rgb_lab "color conversions"
  

• COLOR_RGB2Lab = 45,
  
  

• COLOR_BGR2Luv = 50, //!< convert RGB/BGR to CIE Luv, @ref color_convert_rgb_luv "color conversions"
  

• COLOR_RGB2Luv = 51,
  
• COLOR_BGR2HLS = 52, //!< convert RGB/BGR to HLS (hue lightness saturation) with H range 0..180 if 8 bit image, @ref color_convert_rgb_hls "color conversions"
  

• COLOR_RGB2HLS = 53,
  
  

• COLOR_HSV2BGR = 54, //!< backward conversions HSV to RGB/BGR with H range 0..180 if 8 bit image
  

• COLOR_HSV2RGB = 55,
  
  

• COLOR_Lab2BGR = 56,
  

• COLOR_Lab2RGB = 57,
  
• COLOR_Luv2BGR = 58,
  
• COLOR_Luv2RGB = 59,
  
• COLOR_HLS2BGR = 60, //!< backward conversions HLS to RGB/BGR with H range 0..180 if 8 bit image
  
  

• COLOR_HLS2RGB = 61,
  

• COLOR_BGR2HSV_FULL = 66, //!< convert RGB/BGR to HSV (hue saturation value) with H range 0..255 if 8 bit image, @ref color_convert_rgb_hsv "color conversions"
  

• COLOR_RGB2HSV_FULL = 67,
  
• COLOR_BGR2HLS_FULL = 68, //!< convert RGB/BGR to HLS (hue lightness saturation) with H range 0..255 if 8 bit image, @ref color_convert_rgb_hls "color conversions"
  

• COLOR_RGB2HLS_FULL = 69,
  
  

• COLOR_HSV2BGR_FULL = 70, //!< backward conversions HSV to RGB/BGR with H range 0..255 if 8 bit image
  

• COLOR_HSV2RGB_FULL = 71,
  
• COLOR_HLS2BGR_FULL = 72, //!< backward conversions HLS to RGB/BGR with H range 0..255 if 8 bit image
  

• COLOR_HLS2RGB_FULL = 73,
  
  

• COLOR_LBGR2Lab = 74,
  

• COLOR_LRGB2Lab = 75,
  
• COLOR_LBGR2Luv = 76,
  

• COLOR_LRGB2Luv = 77,
  
  

• COLOR_Lab2LBGR = 78,
  

• COLOR_Lab2LRGB = 79,
  
• COLOR_Luv2LBGR = 80,
  

• COLOR_Luv2LRGB = 81,
  
  

• COLOR_BGR2YUV = 82, //!< convert between RGB/BGR and YUV
  

• COLOR_RGB2YUV = 83,
  
• COLOR_YUV2BGR = 84,
  
• COLOR_YUV2RGB = 85,
  
  

//! YUV 4:2:0 family to RGB
- COLOR_YUV2RGB_NV12 = 90,
- COLOR_YUV2BGR_NV12 = 91,
- COLOR_YUV2RGB_NV21 = 92,
- COLOR_YUV2BGR_NV21 = 93,
- COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21,
- COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21,

• COLOR_YUV2RGBA_NV12 = 94,
  
• COLOR_YUV2BGRA_NV12 = 95,
  
• COLOR_YUV2RGBA_NV21 = 96,
  
• COLOR_YUV2BGRA_NV21 = 97,
  
• COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
  

• COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,
  
  

• COLOR_YUV2RGB_YV12 = 98,
  

• COLOR_YUV2BGR_YV12 = 99,
  
• COLOR_YUV2RGB_IYUV = 100,
  
• COLOR_YUV2BGR_IYUV = 101,
  
• COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV,
  
• COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV,
  
• COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12,
  

• COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12,
  
  

• COLOR_YUV2RGBA_YV12 = 102,
  

• COLOR_YUV2BGRA_YV12 = 103,
  
• COLOR_YUV2RGBA_IYUV = 104,
  
• COLOR_YUV2BGRA_IYUV = 105,
  
• COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
  
• COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
  
• COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12,
  

• COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12,
  
  

• COLOR_YUV2GRAY_420 = 106,
  

• COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
  
• COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
  
• COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
  
• COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
  
• COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
  
• COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
  

• COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420,
  
  

  //! YUV 4:2:2 family to RGB
  - COLOR_YUV2RGB_UYVY = 107,
  - COLOR_YUV2BGR_UYVY = 108,
  //COLOR_YUV2RGB_VYUY = 109,
  //COLOR_YUV2BGR_VYUY = 110,
  - COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
  - COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
  - COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
  - COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,
  
  

• COLOR_YUV2RGBA_UYVY = 111,
  

• COLOR_YUV2BGRA_UYVY = 112,
  //COLOR_YUV2RGBA_VYUY = 113,
  //COLOR_YUV2BGRA_VYUY = 114,
  
• COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
  
• COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
  
• COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
  

• COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,
  
  

• COLOR_YUV2RGB_YUY2 = 115,
  

• COLOR_YUV2BGR_YUY2 = 116,
  
• COLOR_YUV2RGB_YVYU = 117,
  
• COLOR_YUV2BGR_YVYU = 118,
  
• COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
  
• COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
  
• COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
  

• COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,
  
  

• COLOR_YUV2RGBA_YUY2 = 119,
  

• COLOR_YUV2BGRA_YUY2 = 120,
  
• COLOR_YUV2RGBA_YVYU = 121,
  
• COLOR_YUV2BGRA_YVYU = 122,
  
• COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
  
• COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
  
• COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
  

• COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,
  
  

• COLOR_YUV2GRAY_UYVY = 123,
  

• COLOR_YUV2GRAY_YUY2 = 124,
  //CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY,
  
• COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
  
• COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
  
• COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
  
• COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
  
• COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,
  
  

//! alpha premultiplication
- COLOR_RGBA2mRGBA = 125,
- COLOR_mRGBA2RGBA = 126,

//! RGB to YUV 4:2:0 family
- COLOR_RGB2YUV_I420 = 127,
- COLOR_BGR2YUV_I420 = 128,
- COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420,
- COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420,

• COLOR_RGBA2YUV_I420 = 129,
  
• COLOR_BGRA2YUV_I420 = 130,
  
• COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
  
• COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
  
• COLOR_RGB2YUV_YV12 = 131,
  
• COLOR_BGR2YUV_YV12 = 132,
  
• COLOR_RGBA2YUV_YV12 = 133,
  
• COLOR_BGRA2YUV_YV12 = 134,
  
  

//! Demosaicing, see @ref color_convert_bayer "color conversions" for additional information
- COLOR_BayerBG2BGR = 46, //!< equivalent to RGGB Bayer pattern
- COLOR_BayerGB2BGR = 47, //!< equivalent to GRBG Bayer pattern
- COLOR_BayerRG2BGR = 48, //!< equivalent to BGGR Bayer pattern
- COLOR_BayerGR2BGR = 49, //!< equivalent to GBRG Bayer pattern

• COLOR_BayerRGGB2BGR = COLOR_BayerBG2BGR,
  
• COLOR_BayerGRBG2BGR = COLOR_BayerGB2BGR,
  
• COLOR_BayerBGGR2BGR = COLOR_BayerRG2BGR,
  

• COLOR_BayerGBRG2BGR = COLOR_BayerGR2BGR,
  
  

• COLOR_BayerRGGB2RGB = COLOR_BayerBGGR2BGR,
  

• COLOR_BayerGRBG2RGB = COLOR_BayerGBRG2BGR,
  
• COLOR_BayerBGGR2RGB = COLOR_BayerRGGB2BGR,
  

• COLOR_BayerGBRG2RGB = COLOR_BayerGRBG2BGR,
  
  

• COLOR_BayerBG2RGB = COLOR_BayerRG2BGR, //!< equivalent to RGGB Bayer pattern
  

• COLOR_BayerGB2RGB = COLOR_BayerGR2BGR, //!< equivalent to GRBG Bayer pattern
  
• COLOR_BayerRG2RGB = COLOR_BayerBG2BGR, //!< equivalent to BGGR Bayer pattern
  

• COLOR_BayerGR2RGB = COLOR_BayerGB2BGR, //!< equivalent to GBRG Bayer pattern
  
  

• COLOR_BayerBG2GRAY = 86, //!< equivalent to RGGB Bayer pattern
  

• COLOR_BayerGB2GRAY = 87, //!< equivalent to GRBG Bayer pattern
  
• COLOR_BayerRG2GRAY = 88, //!< equivalent to BGGR Bayer pattern
  

• COLOR_BayerGR2GRAY = 89, //!< equivalent to GBRG Bayer pattern
  
  

• COLOR_BayerRGGB2GRAY = COLOR_BayerBG2GRAY,
  

• COLOR_BayerGRBG2GRAY = COLOR_BayerGB2GRAY,
  
• COLOR_BayerBGGR2GRAY = COLOR_BayerRG2GRAY,
  
• COLOR_BayerGBRG2GRAY = COLOR_BayerGR2GRAY,
  
  

//! Demosaicing using Variable Number of Gradients - COLOR_BayerBG2BGR_VNG = 62, //!< equivalent to RGGB Bayer pattern
- COLOR_BayerGB2BGR_VNG = 63, //!< equivalent to GRBG Bayer pattern
- COLOR_BayerRG2BGR_VNG = 64, //!< equivalent to BGGR Bayer pattern
- COLOR_BayerGR2BGR_VNG = 65, //!< equivalent to GBRG Bayer pattern

• COLOR_BayerRGGB2BGR_VNG = COLOR_BayerBG2BGR_VNG,
  
• COLOR_BayerGRBG2BGR_VNG = COLOR_BayerGB2BGR_VNG,
  
• COLOR_BayerBGGR2BGR_VNG = COLOR_BayerRG2BGR_VNG,
  

• COLOR_BayerGBRG2BGR_VNG = COLOR_BayerGR2BGR_VNG,
  
  

• COLOR_BayerRGGB2RGB_VNG = COLOR_BayerBGGR2BGR_VNG,
  

• COLOR_BayerGRBG2RGB_VNG = COLOR_BayerGBRG2BGR_VNG,
  
• COLOR_BayerBGGR2RGB_VNG = COLOR_BayerRGGB2BGR_VNG,
  

• COLOR_BayerGBRG2RGB_VNG = COLOR_BayerGRBG2BGR_VNG,
  
  

• COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG, //!< equivalent to RGGB Bayer pattern
  

• COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG, //!< equivalent to GRBG Bayer pattern
  
• COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG, //!< equivalent to BGGR Bayer pattern
  
• COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG, //!< equivalent to GBRG Bayer pattern
  
  

//! Edge-Aware Demosaicing - COLOR_BayerBG2BGR_EA = 135, //!< equivalent to RGGB Bayer pattern
- COLOR_BayerGB2BGR_EA = 136, //!< equivalent to GRBG Bayer pattern
- COLOR_BayerRG2BGR_EA = 137, //!< equivalent to BGGR Bayer pattern
- COLOR_BayerGR2BGR_EA = 138, //!< equivalent to GBRG Bayer pattern

• COLOR_BayerRGGB2BGR_EA = COLOR_BayerBG2BGR_EA,
  
• COLOR_BayerGRBG2BGR_EA = COLOR_BayerGB2BGR_EA,
  
• COLOR_BayerBGGR2BGR_EA = COLOR_BayerRG2BGR_EA,
  

• COLOR_BayerGBRG2BGR_EA = COLOR_BayerGR2BGR_EA,
  
  

• COLOR_BayerRGGB2RGB_EA = COLOR_BayerBGGR2BGR_EA,
  

• COLOR_BayerGRBG2RGB_EA = COLOR_BayerGBRG2BGR_EA,
  
• COLOR_BayerBGGR2RGB_EA = COLOR_BayerRGGB2BGR_EA,
  

• COLOR_BayerGBRG2RGB_EA = COLOR_BayerGRBG2BGR_EA,
  
  

• COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA, //!< equivalent to RGGB Bayer pattern
  

• COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA, //!< equivalent to GRBG Bayer pattern
  
• COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA, //!< equivalent to BGGR Bayer pattern
  
• COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA, //!< equivalent to GBRG Bayer pattern
  
  

//! Demosaicing with alpha channel
- COLOR_BayerBG2BGRA = 139, //!< equivalent to RGGB Bayer pattern
- COLOR_BayerGB2BGRA = 140, //!< equivalent to GRBG Bayer pattern
- COLOR_BayerRG2BGRA = 141, //!< equivalent to BGGR Bayer pattern
- COLOR_BayerGR2BGRA = 142, //!< equivalent to GBRG Bayer pattern

• COLOR_BayerRGGB2BGRA = COLOR_BayerBG2BGRA,
  
• COLOR_BayerGRBG2BGRA = COLOR_BayerGB2BGRA,
  
• COLOR_BayerBGGR2BGRA = COLOR_BayerRG2BGRA,
  

• COLOR_BayerGBRG2BGRA = COLOR_BayerGR2BGRA,
  
  

• COLOR_BayerRGGB2RGBA = COLOR_BayerBGGR2BGRA,
  

• COLOR_BayerGRBG2RGBA = COLOR_BayerGBRG2BGRA,
  
• COLOR_BayerBGGR2RGBA = COLOR_BayerRGGB2BGRA,
  

• COLOR_BayerGBRG2RGBA = COLOR_BayerGRBG2BGRA,
  
  

• COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA, //!< equivalent to RGGB Bayer pattern
  

• COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA, //!< equivalent to GRBG Bayer pattern
  
• COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA, //!< equivalent to BGGR Bayer pattern
  

• COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA, //!< equivalent to GBRG Bayer pattern
  
  

• COLOR_COLORCVT_MAX = 143
  

---

1. 如下
   - COLOR_BGR2BGRA = 0, //!< add alpha channel to RGB or BGR image
   - COLOR_RGB2RGBA = COLOR_BGR2BGRA,
   
    ↩