Calculate the histogram of the second channel in a three-channel image. Use an optional bin size and a range of 0 to 100 for possible values of the second channel.
Create a histogram that can be used with the calcBackProject function to extract the darkest pixels from a grayscale image. Consider the darkest 25% possible pixel values as the grayscale intensities we are looking to extract.
In the previous question, what if we needed the darkest and brightest 25% to be excluded, instead of extracted, in a mask?
What is the hue value of the color red? How much should it be shifted to get the color blue?
Create a hue histogram that can be used to extract red-colored pixels from an image. Consider an offset of 50 for pixels that are considered reddish. Finally, visualize the hue histogram calculated.
Calculate the integral of a histogram.
Perform histogram equalization on a color image. Note that the equalizeHist function only supports histogram equalization of single-channel 8-bit grayscale images.
