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Converting Color to Grayscale Using ATL::CImage

daily insider

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5 Nov 2009CPOL

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Demonstrates how the ATL::CImage class can be used to do color-to-grayscale conversion on images.

Introduction

This is just a simple MFC application that demonstrates how you can use the ATL::CImage class to do color-to-grayscale conversion.

Background

Conversion is done by:

obtaining the red, green, and blue values in each pixel's color information,
adding together 30% of the red value, 59% of the green value, and 11% of the blue value,
using the sum obtained in step 2 as the new red, green, and blue values.

Using the Code

There are two implementations for doing the conversion:

MakeGrayscale_Slow() --> simple but slow
MakeGrayscale_Fast() --> a little complicated but fast

Points of Interest

MakeGrayscale_Slow() and MakeGrayscale_Fast() produce different grayscales for the same color image. I have no idea why this happens. Anyone who knows?

History

2009/11/06 - Uploaded this article

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

daily insider

Philippines

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Comments and Discussions

Mahdi Nejadsahebi1-Feb-14 23:07

Mahdi Nejadsahebi

1-Feb-14 23:07

You didn't put source code to understand better,but thanks.

SteveScanlon9-Nov-09 9:24

9-Nov-09 9:24

The article is full of errors and a very amateurish approach.

Nick Gorlov9-Nov-09 0:36

9-Nov-09 0:36

It's not an article. You just posted an example of converting 24bpp image to grayscale with great quantity of mistakes Smile | :)

Smile | :)

.
Look throw the codeproject, there are a lot of examples of such convertation. There is nothing new in your post.

"Anyone who knows?"

Axel Rietschin6-Nov-09 15:32

6-Nov-09 15:32

The triplet's order is BGR in memory, not RGB.

Some comments [modified]

Popular

mluri6-Nov-09 0:08

6-Nov-09 0:08

Hi, Just a few comments:

First, the article title says "Converting Color to Grayscale Using ATL::CImage", while you are using ATL::CImage to store the image and converting it yourself.

Next, you are getting different images with your different algorithms because you are taking the separate color values wrong in the fast method. RGB values are not stored as RGB but rather as BGR (take a look at how the RGB macro is defined). So it should be:

lAdrs  = y * pitch + x*3;
bBlue   = *( pInImage + lAdrs );
bGreen = *( pInImage + lAdrs + 1 );
bRed  = *( pInImage + lAdrs + 2 );

Finally, maybe you should round the gray value to the nearest integer, not just truncate it to the integer part of the double value. It won't make such a difference, visually, but it will be more correct. Like this:

gray = (R*0.587 + G*0.299 + B*0.114) + 0.5;

[EDIT]
An alternate (and in my opinion better) way of getting the address of the pixel is through CImage::GetPixelAddress(). It takes into account the pitch and the bits per pixel, so you don't have to do the math yourself.

modified on Friday, November 6, 2009 6:35 AM

Re: Some comments

Darryl Bryk9-Aug-10 11:45

9-Aug-10 11:45

Just a side note on using CImage::GetPixelAddress()...

I haven't seen anybody write on this topic here (maybe I should), but for really fast access to the pixels in a CImage (assuming you want to process every pixel the same way) get a pointer to CImage::GetBits and simply increment the pointer to access each pixel. If the image is a typical bottom-up, like bmp's, then you will need to first covert the image to a top-down style bitmap (use the CImage::Create(sizex, -(int)sizey, 32, 0) with a neg. y size and copy the rows into it), but then every time you modify it you have extremely fast manipulations. In my image processing app. I can do entire image normalizations, thresholds, and color mappings, interactively, while moving a slider! For larger images it lags the slider a bit, but makes it easier to see what your doing to the image in almost real-time.

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