According to Wikipedia, Contrast is the difference in luminance or color that makes an object distinguishable from other objects within the same field of view.
Take a look at the images shown below
Clearly, the left image has a low contrast because it is difficult to identify the details present in the image as compared to the right image.
A real life example can be of a sunny and a foggy day. On a sunny day, everything looks clear to us, thus has a high contrast, as compared to a foggy day, where everything looks nearly of the same intensity (dull, washed-out grey look).
A more valid way to check whether an image has a low or high contrast is to plot the image histogram. Let’s plot the histogram for the above images
Clearly, from the left image histogram, we can see that the image intensity values are located in a narrow range. Because it’s hard to distinguish nearly the same intensity values (See below figure, 150 and 148 are hard to distinguish as compared to 50 and 200), thus the left image has low contrast.
The right histogram increases this gap between the intensity values and Whoo! the details in the image are now much more perceivable to us and thus yields a high contrast image.
So, for the high contrast, the image histogram should span the entire dynamic range as shown above by the right histogram. In the next blogs, we will learn different methods to do this.
There is another naive approach where we subtract the max and min intensity values and based on this difference we judge the image contrast. I will not recommend following this as this may get affected by the outliers (we will discuss in the next blogs). So, always plot the histogram to check.
Till now, we discussed contrast but we didn’t discuss the cause of low contrast images.
Low contrast images can result from Poor illumination, lack of dynamic range in the imaging sensor or even wrong setting of lens aperture during image acquisition etc.
When performing Contrast enhancement, you must first decide whether you want to do global or local contrast enhancement. Global means increasing the contrast of the whole image, While in local we divide the image into small regions and perform contrast enhancement on these regions independently. Don’t Worry, we will discuss these in detail in the next blogs.
This concept has been beautifully illustrated by the figure shown below( Taken from OpenCV Documentation)
Clearly, on global enhancement, the details present on the face of the statue are lost. While these are preserved in the local enhancement. So you need to be careful when selecting these methods.
In the next blog, we will discuss the methods used to transform a low contrast image into a high contrast image. Hope you enjoy reading.
If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.