### 机器视觉代写|图像处理作业代写Image Processing代考|Digital Image Processing Preliminaries

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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 机器视觉代写|图像处理作业代写Image Processing代考|Digital Image Processing Preliminaries

A digital image in a 2-dimensional discrete space is the sampling and quantization of a 2 -dimensional continuous space, being a projection of a picture of objects and background in 3-dimensional space. A digital image is composed of 2 -dimensional array elements arranged in rows and columns. Those elements are the so-called pixels, and each of them holds a particular value to represent the picture at its location.
For a mathematical expression, a digital image can be represented as a function $f(x, y)$, where $(x, y)$ are integers and $f$ is a mapping that assigns an intensity value to each distinct pair of coordinates $(x, y)$. A digital image with $M$ rows and $N$ columns, which we say that the image is of size $M \times N$, can also be represented as a matrix:
$$f=\left[\begin{array}{cccccc} f(1,1) & f(1,2) & \cdots & f(1, y) & \cdots & f(1, N) \ f(2,1) & f(2,2) & \cdots & f(2, y) & \cdots & f(2, N) \ \vdots & \vdots & \ddots & \vdots & \ddots & \vdots \ f(x, 1) & f(x, 2) & \cdots & f(x, y) & \cdots & f(x, N) \ \vdots & \vdots & \ddots & \vdots & \ddots & \vdots \ f(M, 1) & f(M, 2) & \cdots & f(M, y) & \cdots & f(M, N) \end{array}\right]$$
where $f(x, y)(1 \leq x \leq M, 1 \leq y \leq N)$ is the finite and quantized value that represent the gray scale or color of the image at the point $(x, y)$.

In this chapter, some beforehand knowledge about digital image processing relevant to the sea ice image processing algorithms presented in this book is introduced.

## 机器视觉代写|图像处理作业代写Image Processing代考|The CMY and CMYK color spaces

The CMY (cyan, magenta, and yellow) color model is a subtractive color representation. It is typically used in color printing because cyan, magenta, and yellow are the primary colors of pigments. The CMY color model can be transformed from the RGB model by:
$$\left[\begin{array}{c} C \ M \ Y \end{array}\right]=\left[\begin{array}{l} 1 \ 1 \ 1 \end{array}\right]-\left[\begin{array}{l} R \ G \ B \end{array}\right]$$
where the tristimulus values in the RGB color model are normalized to the range $[0,1]$. Figure $2.4$ presents the CMY components of the color image shown in Figure $2.3$.

In practice, to produce true black color for printing without using excessive amounts of CMY pigments, black, called the key (K), is added as a fourth color, giving rise to the CMYK color model. The conversion between the CMYK and RGB is given by [121]:
$$\left[\begin{array}{l} C \ M \ Y \ K \end{array}\right]=\left[\begin{array}{l} 1 \ 1 \ 1 \ 0 \end{array}\right]-\left[\begin{array}{l} R \ G \ B \ 0 \end{array}\right]-K_{b}\left[\begin{array}{c} u \ u \ u \ -b \end{array}\right]$$
where
$$K_{b}=\min {1-R, 1-G, 1-B}$$
and $u(0 \leq u \leq 1)$ is the under-color removal factor, and $b(0 \leq b \leq 1)$ is the darkness factor.

## 机器视觉代写|图像处理作业代写Image Processing代考|The HSI color space

Alternative to the RGB, CMY and CMYK color spaces, a hue-saturation color coding method, HSI (hue, saturation, and intensity), is also commonly used, particularly in the image processing algorithms based on color descriptions. Hue is an attribute that describes a pure color, while saturation (purity) is a measure of the degree to which pure color is diluted by white light. The HSI color model decouples the intensity component from the hue and saturation in a color image [49], and it can be obtained from the RGB color model by [121]:
$$\begin{gathered} {\left[\begin{array}{c} I \ V_{1} \ V_{2} \end{array}\right]=\left[\begin{array}{ccc} \frac{1}{3} & \frac{1}{3} & \frac{1}{3} \ \frac{-1}{\sqrt{6}} & \frac{-1}{\sqrt{6}} & \frac{2}{\sqrt{6}} \ \frac{1}{\sqrt{6}} & \frac{-1}{\sqrt{6}} & 0 \end{array}\right]\left[\begin{array}{l} R \ G \ B \end{array}\right]} \ H=\arctan \left(\frac{V_{2}}{V_{1}}\right) \ S=\sqrt{V_{1}^{2}+V_{2}^{2}} \end{gathered}$$
Figure $2.5$ presents the HSI components of the color image shown in Figure $2.3$.

## 机器视觉代写|图像处理作业代写Image Processing代考|Digital Image Processing Preliminaries

F=[F(1,1)F(1,2)⋯F(1,是)⋯F(1,ñ) F(2,1)F(2,2)⋯F(2,是)⋯F(2,ñ) ⋮⋮⋱⋮⋱⋮ F(X,1)F(X,2)⋯F(X,是)⋯F(X,ñ) ⋮⋮⋱⋮⋱⋮ F(米,1)F(米,2)⋯F(米,是)⋯F(米,ñ)]

## 机器视觉代写|图像处理作业代写Image Processing代考|The CMY and CMYK color spaces

CMY（青色、品红色和黄色）颜色模型是一种减色表示。它通常用于彩色印刷，因为青色、品红色和黄色是颜料的原色。CMY 颜色模型可以通过以下方式从 RGB 模型转换：
[C 米 是]=[1 1 1]−[R G 乙]

[C 米 是 ķ]=[1 1 1 0]−[R G 乙 0]−ķb[在 在 在 −b]

ķb=分钟1−R,1−G,1−乙

## 机器视觉代写|图像处理作业代写Image Processing代考|The HSI color space

[一世 在1 在2]=[131313 −16−1626 16−160][R G 乙] H=反正切⁡(在2在1) 小号=在12+在22

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## MATLAB代写

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