MATLAB高级图像处理：理论与实战指南

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"本篇论文【信息技术】【2012.05】，由芬兰米凯利应用科学大学的Justyna Inglot撰写，是一篇65页的高级图像处理学士论文。论文探讨的主题是"Advanced Image Processing with Matlab"，针对计算机图形学领域的快速发展，尤其是图像处理技术的应用和开发。Matlab被选为研究的核心工具，因其提供了高级编程语言、丰富的专业工具箱和易用的图形用户界面设计能力。文章首先介绍了计算机图形学的基础概念和当前市场上的图像处理应用现状，强调了寻找能有效结合图像处理功能与编程技术的软件需求。作者通过Matlab的介绍，展示了它在图像处理领域的强大优势，如高效的数据处理和分析能力，以及GUI设计的便捷性。论文的重点在于深入探讨如何使用MATLAB内置的GUIDE工具创建图形用户界面，以便于用户操作和交互。理论知识与实践相结合，论文中的每个理论环节都伴随着具体图像处理应用实例的演示。软件开发过程中的测试环节也得到了充分重视，作者提供了多个测试场景和实际操作案例，确保了软件的可靠性和效能。通过此论文，作者不仅展示了MATLAB在图像处理领域的实用性，还为图像处理技术的未来发展指明了方向，提出了创新性的实现思路和技术可能。这篇论文不仅是对Matlab图像处理工具箱的实用指南，也是对图像处理技术在实际项目中应用的一次深入探索，对于对计算机图形学和Matlab感兴趣的读者来说，具有很高的参考价值。"

Subtractive color model operates on rules opposite to additive systems. Three numeri-

cal values are subtracted from white in order to create new color tones. Primary colors

used here are cyan, magenta and yellow. More colors are mixed, more close to black

new color is. Subtractive model is commonly used while printing. Both systems are

complementary to each other (Ozimek, Lectures from Computer Graphics on Cracow

University of Technology, 2009b).

There are three well known, common color systems: RGB, CMYK and HSV. First

one, additive system RGB stands for red (R), green (G) and blue (B). It is widely used

for any image file formats. Graphics that is using RGB model represents each pixel as

a three numerical values in brackets. First value is the amount of red, second stands

for green and the third one is blue. Those values are used to create color presented on

the screen. All values can’t outreach 255 and can’t be lower than 0. For example trip-

let (0,0,0) stands for black when (255,255,255) goes as white color. Every other mix

of values stands for different color. For better understanding how colors are changing,

Figure 1 presents the cube of RGB color. Axe X stands for red, Y for green and Z for

blue. With moving along all axes different colors can be created.

Figure 1. Cube of RGB color model (Wikimedia Commons [referred 25.03.2010])

What is worth mentioning, RGB systems are directed at device. It means that on dif-

ferent device colors can be seen differently. To make printing world easier other color

Therefore bitmap is commonly used to store black-white images. Other definition says

that each pixel may contain more bits to store the information. For example eight bits

per pixel can be used to code 256 tones of grayscale (www.wisegeek.com [referred

25.03.2010]).

Grayscale is a colormap that usually stores information about the image in eight bits

per pixel. Like mentioned before, with eight bits it is possible to create scale of 256

shades of gray. Sometimes grayscale is described as carrying only one pixel which

stores information about brightness of black. Result is a scale of different tones of

gray. All range of gray may be represented as RGB triple value. All three numbers

have to be equal, for example (123,123,123) or (3,3,3).

Another useful colormap is called indexed colormap. Each pixel of image stores in-

formation about index to the place in colors array, for example set by the user. The

biggest palette can contain 256 colors. Indexed color is very useful. It saves comput-

er’s memory and disk space. Smaller color palettes can be used to represent icons and

pictures with small range of colors. Indexed colormap also supports setting transparent

color. Picking transparent pixels is very helpful when it comes to images with irregu-

lar shapes. Thanks to that feature object on image can be put on a background without

necessity of deleting rectangular shape (Vanderburg et al. 1996, chapter 12).

More advanced colormap is called truecolor. Information about the image is stored in

24 bits, which equals 3 bytes. Each color from RGB model gets 8 bits for storage of

information about shade and channel of color. Truecolor system uses at least 256

tones of each color (red, green and blue), which gives huge range of usable colors -

16.777.216 possible variations. This system is often used in high quality photographs

and complex images (Ozimek, lectures from Digital image processing, 2010a).

There are plenty of colormaps but one more worth describing is called highcolor. It

offers very wide range of colors, bigger than in truecolor system. The description of

point on the image contains 16 bits of information. This amount allows to code from 0

to 65535 different values for one RGB color, which gives 65535*65535*65535 color

variations. The precision in highcolor system is twice much better than in truecolor.

Mostly because that highcolor is used while photographing more prevalent colors, for

example skin tones or skies (Ozimek, lectures from Digital image processing, 2010a).

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