How to resolve the algorithm Grayscale image step by step in the Julia programming language
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:
-
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 fromima
using thergb2gray
function.
-
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. -
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. -
Grayscale Conversion: The code then demonstrates the usage of the
rgb2gray
andgray2rgb
functions by performing the following steps:- Converted
ima
(the RGB image) to grayscale usingrgb2gray
, resulting inimb
. - Reconverted
imb
(the grayscale image) back to RGB usinggray2rgb
, resulting inimc
. - Wrote
imc
to a new file "grayscale_image_rc.png."
- Converted
-
Alternative Grayscale Conversion: The code also demonstrates an alternative method of converting an RGB image to grayscale using the
convert
function from theColor
module. This method internally uses the same conversion formula asrgb2gray
and directly assigns the resulting grayscale values to a newGray{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")
You may also check:How to resolve the algorithm Polymorphism step by step in the D programming language
You may also check:How to resolve the algorithm Repeat step by step in the Phixmonti programming language
You may also check:How to resolve the algorithm Object serialization step by step in the Haskell programming language
You may also check:How to resolve the algorithm Fibonacci word/fractal step by step in the PARI/GP programming language
You may also check:How to resolve the algorithm Create a file step by step in the Crystal programming language