8.4 KiB
Color conversions
See cv::cvtColor and cv::ColorConversionCodes @todo document other conversion modes
@anchor color_convert_rgb_gray RGB \f$\leftrightarrow\f$ GRAY
Transformations within RGB space like adding/removing the alpha channel, reversing the channel order, conversion to/from 16-bit RGB color (R5:G6:B5 or R5:G5:B5), as well as conversion to/from grayscale using: \f[\text{RGB[A] to Gray:} \quad Y \leftarrow 0.299 \cdot R + 0.587 \cdot G + 0.114 \cdot B\f] and \f[\text{Gray to RGB[A]:} \quad R \leftarrow Y, G \leftarrow Y, B \leftarrow Y, A \leftarrow \max (ChannelRange)\f] The conversion from a RGB image to gray is done with: @code cvtColor(src, bwsrc, cv::COLOR_RGB2GRAY); @endcode More advanced channel reordering can also be done with cv::mixChannels. @see cv::COLOR_BGR2GRAY, cv::COLOR_RGB2GRAY, cv::COLOR_GRAY2BGR, cv::COLOR_GRAY2RGB
@anchor color_convert_rgb_xyz RGB \f$\leftrightarrow\f$ CIE XYZ.Rec 709 with D65 white point
\f[\begin{bmatrix} X \ Y \ Z \end{bmatrix} \leftarrow \begin{bmatrix} 0.412453 & 0.357580 & 0.180423 \ 0.212671 & 0.715160 & 0.072169 \ 0.019334 & 0.119193 & 0.950227 \end{bmatrix} \cdot \begin{bmatrix} R \ G \ B \end{bmatrix}\f] \f[\begin{bmatrix} R \ G \ B \end{bmatrix} \leftarrow \begin{bmatrix} 3.240479 & -1.53715 & -0.498535 \ -0.969256 & 1.875991 & 0.041556 \ 0.055648 & -0.204043 & 1.057311 \end{bmatrix} \cdot \begin{bmatrix} X \ Y \ Z \end{bmatrix}\f] \f$X\f$, \f$Y\f$ and \f$Z\f$ cover the whole value range (in case of floating-point images, \f$Z\f$ may exceed 1).
@see cv::COLOR_BGR2XYZ, cv::COLOR_RGB2XYZ, cv::COLOR_XYZ2BGR, cv::COLOR_XYZ2RGB
@anchor color_convert_rgb_ycrcb RGB \f$\leftrightarrow\f$ YCrCb JPEG (or YCC)
\f[Y \leftarrow 0.299 \cdot R + 0.587 \cdot G + 0.114 \cdot B\f] \f[Cr \leftarrow (R-Y) \cdot 0.713 + delta\f] \f[Cb \leftarrow (B-Y) \cdot 0.564 + delta\f] \f[R \leftarrow Y + 1.403 \cdot (Cr - delta)\f] \f[G \leftarrow Y - 0.714 \cdot (Cr - delta) - 0.344 \cdot (Cb - delta)\f] \f[B \leftarrow Y + 1.773 \cdot (Cb - delta)\f] where \f[delta = \left { \begin{array}{l l} 128 & \mbox{for 8-bit images} \ 32768 & \mbox{for 16-bit images} \ 0.5 & \mbox{for floating-point images} \end{array} \right .\f] Y, Cr, and Cb cover the whole value range. @see cv::COLOR_BGR2YCrCb, cv::COLOR_RGB2YCrCb, cv::COLOR_YCrCb2BGR, cv::COLOR_YCrCb2RGB
@anchor color_convert_rgb_hsv RGB \f$\leftrightarrow\f$ HSV
In case of 8-bit and 16-bit images, R, G, and B are converted to the floating-point format and scaled to fit the 0 to 1 range.
\f[V \leftarrow max(R,G,B)\f] \f[S \leftarrow \fork{\frac{V-min(R,G,B)}{V}}{if (V \neq 0)}{0}{otherwise}\f] \f[H \leftarrow \forkthree{{60(G - B)}/{(V-min(R,G,B))}}{if (V=R)}{{120+60(B - R)}/{(V-min(R,G,B))}}{if (V=G)}{{240+60(R - G)}/{(V-min(R,G,B))}}{if (V=B)}\f] If \f$H<0\f$ then \f$H \leftarrow H+360\f$ . On output \f$0 \leq V \leq 1\f$, \f$0 \leq S \leq 1\f$, \f$0 \leq H \leq 360\f$ .
The values are then converted to the destination data type:
- 8-bit images: \f$V \leftarrow 255 V, S \leftarrow 255 S, H \leftarrow H/2 \text{(to fit to 0 to 255)}\f$
- 16-bit images: (currently not supported) \f$V <- 65535 V, S <- 65535 S, H <- H\f$
- 32-bit images: H, S, and V are left as is
@see cv::COLOR_BGR2HSV, cv::COLOR_RGB2HSV, cv::COLOR_HSV2BGR, cv::COLOR_HSV2RGB
@anchor color_convert_rgb_hls RGB \f$\leftrightarrow\f$ HLS
In case of 8-bit and 16-bit images, R, G, and B are converted to the floating-point format and scaled to fit the 0 to 1 range.
\f[V_{max} \leftarrow {max}(R,G,B)\f]
\f[V_{min} \leftarrow {min}(R,G,B)\f]
\f[L \leftarrow \frac{V_{max} + V_{min}}{2}\f]
\f[S \leftarrow \fork { \frac{V_{max} - V_{min}}{V_{max} + V_{min}} }{if L < 0.5 }
{ \frac{V_{max} - V_{min}}{2 - (V_{max} + V_{min})} }{if L \ge 0.5 }\f]
\f[H \leftarrow \forkthree {{60(G - B)}/{(V_{max}-V_{min})}}{if V_{max}=R }
{{120+60(B - R)}/{(V_{max}-V_{min})}}{if V_{max}=G }
{{240+60(R - G)}/{(V_{max}-V_{min})}}{if V_{max}=B }\f]
If \f$H<0\f$ then \f$H \leftarrow H+360\f$ . On output \f$0 \leq L \leq 1\f$, \f$0 \leq S \leq
1\f$, \f$0 \leq H \leq 360\f$ .
The values are then converted to the destination data type:
- 8-bit images: \f$V \leftarrow 255 \cdot V, S \leftarrow 255 \cdot S, H \leftarrow H/2 ; \text{(to fit to 0 to 255)}\f$
- 16-bit images: (currently not supported) \f$V <- 65535 \cdot V, S <- 65535 \cdot S, H <- H\f$
- 32-bit images: H, S, V are left as is
@see cv::COLOR_BGR2HLS, cv::COLOR_RGB2HLS, cv::COLOR_HLS2BGR, cv::COLOR_HLS2RGB
@anchor color_convert_rgb_lab RGB \f$\leftrightarrow\f$ CIE L*a*b*
In case of 8-bit and 16-bit images, R, G, and B are converted to the floating-point format and scaled to fit the 0 to 1 range.
\f[\vecthree{X}{Y}{Z} \leftarrow \vecthreethree{0.412453}{0.357580}{0.180423}{0.212671}{0.715160}{0.072169}{0.019334}{0.119193}{0.950227} \cdot \vecthree{R}{G}{B}\f] \f[X \leftarrow X/X_n, \text{where} X_n = 0.950456\f] \f[Z \leftarrow Z/Z_n, \text{where} Z_n = 1.088754\f] \f[L \leftarrow \fork{116Y^{1/3}-16}{for (Y>0.008856)}{903.3Y}{for (Y \le 0.008856)}\f] \f[a \leftarrow 500 (f(X)-f(Y)) + delta\f] \f[b \leftarrow 200 (f(Y)-f(Z)) + delta\f] where \f[f(t)= \fork{t^{1/3}}{for (t>0.008856)}{7.787 t+16/116}{for (t\leq 0.008856)}\f] and \f[delta = \fork{128}{for 8-bit images}{0}{for floating-point images}\f]
This outputs \f$0 \leq L \leq 100\f$, \f$-127 \leq a \leq 127\f$, \f$-127 \leq b \leq 127\f$ . The values are then converted to the destination data type:
- 8-bit images: \f$L \leftarrow L*255/100, ; a \leftarrow a + 128, ; b \leftarrow b + 128\f$
- 16-bit images: (currently not supported)
- 32-bit images: L, a, and b are left as is
@see cv::COLOR_BGR2Lab, cv::COLOR_RGB2Lab, cv::COLOR_Lab2BGR, cv::COLOR_Lab2RGB
@anchor color_convert_rgb_luv RGB \f$\leftrightarrow\f$ CIE L*u*v*
In case of 8-bit and 16-bit images, R, G, and B are converted to the floating-point format and scaled to fit 0 to 1 range.
\f[\vecthree{X}{Y}{Z} \leftarrow \vecthreethree{0.412453}{0.357580}{0.180423}{0.212671}{0.715160}{0.072169}{0.019334}{0.119193}{0.950227} \cdot \vecthree{R}{G}{B}\f] \f[L \leftarrow \fork{116Y^{1/3} - 16}{for (Y>0.008856)}{903.3 Y}{for (Y\leq 0.008856)}\f] \f[u' \leftarrow 4X/(X + 15Y + 3 Z)\f] \f[v' \leftarrow 9Y/(X + 15Y + 3 Z)\f] \f[u \leftarrow 13L*(u' - u_n) \quad \text{where} \quad u_n=0.19793943\f] \f[v \leftarrow 13L(v' - v_n) \quad \text{where} \quad v_n=0.46831096\f]
This outputs \f$0 \leq L \leq 100\f$, \f$-134 \leq u \leq 220\f$, \f$-140 \leq v \leq 122\f$ .
The values are then converted to the destination data type:
- 8-bit images: \f$L \leftarrow 255/100 L, ; u \leftarrow 255/354 (u + 134), ; v \leftarrow 255/262 (v + 140)\f$
- 16-bit images: (currently not supported)
- 32-bit images: L, u, and v are left as is
The above formulae for converting RGB to/from various color spaces have been taken from multiple sources on the web, primarily from the Charles Poynton site http://www.poynton.com/ColorFAQ.html
@see cv::COLOR_BGR2Luv, cv::COLOR_RGB2Luv, cv::COLOR_Luv2BGR, cv::COLOR_Luv2RGB
@anchor color_convert_bayer Bayer \f$\rightarrow\f$ RGB
The Bayer pattern is widely used in CCD and CMOS cameras. It enables you to get color pictures from a single plane where R,G, and B pixels (sensors of a particular component) are interleaved as follows:
The output RGB components of a pixel are interpolated from 1, 2, or 4 neighbors of the pixel having the same color. There are several modifications of the above pattern that can be achieved by shifting the pattern one pixel left and/or one pixel up. The two letters \f$C_1\f$ and \f$C_2\f$ in the conversion constants CV_Bayer \f$C_1 C_2\f$ 2BGR and CV_Bayer \f$C_1 C_2\f$ 2RGB indicate the particular pattern type. These are components from the second row, second and third columns, respectively. For example, the above pattern has a very popular "BG" type.
@see cv::COLOR_BayerBG2BGR, cv::COLOR_BayerGB2BGR, cv::COLOR_BayerRG2BGR, cv::COLOR_BayerGR2BGR, cv::COLOR_BayerBG2RGB, cv::COLOR_BayerGB2RGB, cv::COLOR_BayerRG2RGB, cv::COLOR_BayerGR2RGB