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

Published on 22 June 2024 08:30 PM

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

This Julia code performs grayscale conversion on an image and converts a grayscale image to an RGB image. Here's a detailed explanation of the code:

  1. Loading the Images: The code begins by loading two images using the imread function:

    • ima is an RGB image loaded from the file "grayscale_image_color.png."
    • imb is a grayscale image converted from ima using the rgb2gray function.
  2. rgb2gray Function: This function converts an RGB image to a grayscale image. It does this by calculating the weighted average of the red, green, and blue channels of each pixel in the RGB image. The resulting grayscale image is then clamped between 0.0 (black) and 1.0 (white) to ensure valid pixel values.

  3. gray2rgb Function: This function converts a grayscale image to an RGB image. It checks if the input image has the "Gray" colorspace, indicating that it's already grayscale. If so, it directly returns the input image. Otherwise, it creates a new RGB image by assigning the same grayscale value to all three channels (red, green, and blue) for each pixel.

  4. Grayscale Conversion: The code then demonstrates the usage of the rgb2gray and gray2rgb functions by performing the following steps:

    • Converted ima (the RGB image) to grayscale using rgb2gray, resulting in imb.
    • Reconverted imb (the grayscale image) back to RGB using gray2rgb, resulting in imc.
    • Wrote imc to a new file "grayscale_image_rc.png."
  5. Alternative Grayscale Conversion: The code also demonstrates an alternative method of converting an RGB image to grayscale using the convert function from the Color module. This method internally uses the same conversion formula as rgb2gray and directly assigns the resulting grayscale values to a new Gray{Ufixed8} image. The converted image is then written to a file named "grayscale_image_julia.png."

Source code in the julia programming language

using Color, Images, FixedPointNumbers

const M_RGB_Y = reshape(Color.M_RGB_XYZ[2,:], 3)

function rgb2gray(img::Image)
    g = red(img)*M_RGB_Y[1] + green(img)*M_RGB_Y[2] + blue(img)*M_RGB_Y[3]
    g = clamp(g, 0.0, 1.0)
    return grayim(g)
end

function gray2rgb(img::Image)
    colorspace(img) == "Gray" || return img
    g = map((x)->RGB{Ufixed8}(x, x, x), img.data)
    return Image(g, spatialorder=spatialorder(img))
end
 
ima = imread("grayscale_image_color.png")
imb = rgb2gray(ima)
imc = gray2rgb(imb)
imwrite(imc, "grayscale_image_rc.png")


using Color, Images, FixedPointNumbers

ima = imread("grayscale_image_color.png")
imb = convert(Image{Gray{Ufixed8}}, ima)
imwrite(imb, "grayscale_image_julia.png")


  

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