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Feature
REALGraphics
Working With Histograms
Issue: 6.5 (July/August 2008)
Author: JC Cruz
Article Description: No description available.
Article Length (in bytes): 25,038
Starting Page Number: 21
RBD Number: 6510
Resource File(s):
6510.zip Updated: Tuesday, July 1, 2008 at 11:42 AM
Related Web Link(s):
RBDeveloper.com
http://en.wikipedia.org/wiki/SMPTE_color_bars
http://apollo.sese.asu.edu
http://marsrovers.jpl.nasa.gov/home/index.html
http://www-128.ibm.com/developerworks/rational/library/content/RationalEdge/sep04/bell/
http://homepages.inf.ed.ac.uk/rbf/HIPR2/histeq.htm
http://homepages.inf.ed.ac.uk/rbf/HIPR2/stretch.htm
http://en.wikipedia.org/wiki/Image_histogram
http://en.wikipedia.org/wiki/Histogram_equalization
Known Limitations: None
Excerpt of article text...
In today's REALGraphics article, we will learn the basics behind an image histogram. First, we study the concept of a histogram and how it relates to image data. We then explore two ways of modifying the histogram data. Next, we build a set of REALbasic classes that will build and manage an image's histogram data. And then we will use these classes to analyze a handful of test images.
The Image Histogram
We all know that all digital images are comprised of a series of dots called pixels (short for "picture elements"). We also know that pixel depth determines the number of colors it can display. For instance, pixels in a black and white have a depth that is exactly 1 bit, where 1 is white, and 0 is black. The pixels in a CGA image, which has only 4 colors, will have a depth of 2 bits. Most modern images, such as those handled by REALbasic, use pixels that are 24-bits in depth. As a result, these pixels can display up to 16777216 colors, sufficient for most photo-quality work.
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Article copyrighted by REALbasic Developer magazine. All rights reserved.
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