How to resolve the algorithm Grayscale image step by step in the PureBasic programming language

Published on 12 May 2024 09:40 PM
#Purebasic

How to resolve the algorithm Grayscale image step by step in the PureBasic programming language

Table of Contents

Problem Statement

Many image processing algorithms are defined for grayscale (or else monochromatic) images.

Extend the data storage type defined on this page to support grayscale images. Define two operations, one to convert a color image to a grayscale image and one for the backward conversion. To get luminance of a color use the formula recommended by CIE: When using floating-point arithmetic make sure that rounding errors would not cause run-time problems or else distorted results when calculated luminance is stored as an unsigned integer.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Grayscale image step by step in the PureBasic programming language

Source code in the purebasic programming language

Procedure ImageGrayout(image)
  Protected w, h, x, y, r, g, b, gray, color
  
  w = ImageWidth(image)
  h = ImageHeight(image)
  StartDrawing(ImageOutput(image))
  For x = 0 To w - 1
    For y = 0 To h - 1
      color = Point(x, y)
      r    = Red(color)
      g    = Green(color)
      b    = Blue(color)
      gray = 0.2126*r + 0.7152*g + 0.0722*b
      Plot(x, y, RGB(gray, gray, gray)
    Next
  Next
  StopDrawing()
EndProcedure

Procedure ImageToColor(image)
  Protected w, h, x, y, v, gray
  
  w = ImageWidth(image)
  h = ImageHeight(image)
  StartDrawing(ImageOutput(image))
  For x = 0 To w - 1
    For y = 0 To h - 1
      gray = Point(x, y)
      v    = Red(gray) ;for gray, each of the color's components is the same 
      ;color = RGB(0.2126*v, 0.7152*v, 0.0722*v)
      Plot(x, y, RGB(v, v, v))
    Next
  Next
  StopDrawing()
EndProcedure

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