处理过滤器和颜色 [英] Dealing with filters and colour's

问题描述

我要制作如下所示的过滤器此处

• 这些是我的目标筛选器，但是请指导我如何去。


• 我可以如何做这些过滤器？


• 我需要遵循哪些算法？

这是更好和最简单的方法来获得滤镜的RGB和阴影效果。

通过spektre从上面的链接复制图片：

• 源图像是第一行中的第一个相机。

解决方案

很难说从单个非测试屏幕图像。

1.黑白滤镜

• 最简单的不精确的转换是i =（R + G + B）/ 3


• 更好的方法是使用权重i = w0 * R + w1 * G + w2 * B其中w0 + w1 + w2 = 1这些值可以通过一个小的google搜索努力找到

2.其余

• 一些过滤器看起来像指数颜色或加权颜色像这样：

    r = w0 * r; if（r> 255）r = 255; 
   g = w1 * g; if（g> 255）g = 255; 
   b = w2 * b; if（b> 255）b = 255; 
    




• 使用3个滚动条为w0，w1，w2写入一个应用程序< 10>



• 使用上述公式重绘图片


• 经过一些实验，您应该为大多数过滤器找到w0，w1，w2 ...



• 其余的可以是这样的颜色混合：

    r = w00 * r + w01 * g + w02 * b; if（r> 255）r = 255; 
   g = w10 * r + w11 * g + w12 * b; if（g> 255）g = 255; 
   b = w20 * r + w21 * g + w22 * b; if（b> 255）b = 255; 
    




• 或：

    i =（r + g + b）/ 3 
  r = w0 * r + w3 * i; if（r> 255）r = 255; 
   g = w1 * g + w3 * i; if（g> 255）g = 255; 
   b = w2 * b + w3 * i; if（b> 255）b = 255; 
   




btw ：

1.在输入图像中找到测试颜色

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• 对于每个阴影拉制R，G，B强度绘制隐藏图


• 一轴是输入图像颜色强度，另一个是过滤颜色的R，G，B强度


• 那么你应该看到直接使用哪个公式，并且还可以计算它的权重


• 这是红色的超指数运作方式

• 如果线条不是线而是曲线，则使用某种伽马校正


• 更高阶（2,3,4 ...的幂）大多数2的幂就足够了


• 在这种情况下，权重也可以是负的！

某些过滤器可以使用不同的颜色空间

• 调整颜色


• 
  

I want to make filters like shown here

• these are my target filters but can you please guide me how to go for them
• how i can make filters like these?
• which algorithms i need to follow? and which step i need to take as beginner?
• Which is the better and easiest way to get the values of RGB and shades of filters .

copy of image from link above by spektre:

• the source image is the first after camera in the first line.

解决方案

very hard to say from single non test-screen image.

1.the black and white filter

• is easy just convert RGB to intensity i and then instead RGB write iii color.
• the simplest not precise conversion is i=(R+G+B)/3
• but better way is use of weights i=w0*R+w1*G+w2*B where w0+w1+w2=1 the values can be found by a little google search effort

2.the rest

• some filters seem like over exponated colors or weighted colors like this:

  r=w0*r; if (r>255) r=255;
  g=w1*g; if (g>255) g=255;
  b=w2*b; if (b>255) b=255;
  

• write an app with 3 scrollbars for w0,w1,w2 in range <0-10>

• and redraw image with above formula
• after little experimenting you should find w0,w1,w2 for most of the filters ...

• the rest can be mix of colors like this:

  r=w00*r+w01*g+w02*b; if (r>255) r=255;
  g=w10*r+w11*g+w12*b; if (g>255) g=255;
  b=w20*r+w21*g+w22*b; if (b>255) b=255;
  

• or:

  i=(r+g+b)/3
  r=w0*r+w3*i; if (r>255) r=255;
  g=w1*g+w3*i; if (g>255) g=255;
  b=w2*b+w3*i; if (b>255) b=255;
  

btw if you want the closest similarity you can:

1.find test colors in input image

• like R shades, G shades , B shades , RG,RB,BG,RGB shades from 0-255
• then get colors from filtered image at the same position
• draw depedency graphs for each shade draw R,G,B intensities
• one axis is input image color intensity and the other one is R,G,B intensity of filtered color
• then you should see which formula is used directly and can also compute the weights from it
• this is how over-exponation works for Red color

• if the lines are not lines but curves then some kind of gamma correction is used
• so formulas use polynom of higher order (power of 2,3,4...) mostly power of 2 suffice
• in that case the weights can be also negative !!!

some filters could use different color spaces

• for example transform RGB to HSV
• shift hue
• and convert back to RGB
• this will shift colors a little

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