2024年4月10日发(作者：)

1. Translation

 Digital image 数字图像

 Gray level 灰度

 Pixel 象素

 Reduce noise 降噪

 Contrast enhancement 对比度增强

 Image sharpening 图像锐化

 Image smoothing 图像平滑

 Segmentation 分割

 Recognition 识别

 Angiography 血管造影术

 Computerized tomography 计算机断层成像

 Positron emission tomography 正电子发射断层成像

 Ultrasound imaging 超声成像

 First order derivative 一阶微分

 Second order derivative 二阶微分

 Mean 均值

 Random variable 随机变量

 Standard deviation 标准差

 Variance 方差

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Salt-and-pepper noise 椒盐噪声

Median filter 中值滤波

Gradient 梯度

Cutoff frequency 截止频率

 Threshold value 阈值

 Subjective brightness 主观亮度

 Brightness adaptation level 亮度适应级

 Sampling and quantization 采样和量化

 Neutral color 中性色

 Hue 色度

 Saturation 饱和度

 Histogram equalization 直方图均衡化

 Histogram matching 直方图匹配

 Fluorescence microscopy 荧光显微镜

 Dynamic range of an image 图像的动态范围

 Probability density function 概率分布函数

 Cumulative distribution function 累积分布函数

 Smoothing linear filter 平滑线性滤波器

 Full color 真彩色

 Pseudo color 伪彩色

 Electromagnetic spectrum 电磁波谱

 Primary colors of light 光的三元色

 Primary colors of pigments 颜料三元色

 Saturation 饱和度

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Chromaticity diagram 色度图

Monochrome image 单色图像

Normal representation of a line 直线标准式

Region growing 区域增长

 Region splitting and merging 区域分离和合并

 Accumulative difference image 累积差分图像

2. Problems

 Ultrasound imaging (p22 or P44)

The ultrasound system transmits high-frequency sound pulse into the body.

 Euclidean distance, city-block distance, chessboard distance (p68 or P93)

 Example 3.1 and 3.2 (p82-84 or P 135)

 Example 3.6 (p105-108 or 165)

 Compare the response in image between first- and second-order derivatives. (p127

or P169, P717)

 Explain why the discrete histogram equalization technique does not, in general, yield

a flat histogram. (p143 or P215 *3.6)

 What effect would setting to zero the lower-order bit planes have on the histogram

of an image in general? (P143 3.4 or P215 3.5)

 What are the basic steps for filtering in the frequency domain? (P 159 or P285)

 Compare ideal lowpass filter, Butterworth lowpass filter and Gaussian lowpass filter.

(P 167-176 or P291-298)

 Illustrate the use of gray level to color transformations to obtain various degrees of

enhancement. (P309 or P442)

 Introduce one way to slice a color image and separate objects from their

surroundings. ( P 320 or 453)

 Explain why the result of smoothing each RGB component image is different from

the result of smoothing the intensity of the HIS image and converting to RGB? (p330

or P462 because……)

 How would you implement the color equivalent of gray scale histogram matching?

(P347 6.24 or 481 6.24)

 How do you go about eliminating the components in figure that are not part of the

line oriented at -45

0

. (P570 or P721)

 Explain why the Laplacian generally is not used in its original form for edge

detection. There are several reasons: sensitive to noise, produce double edges, and

unable to detect edge direction. (p582 the third version has no information)

 Compare edges in gradient image and zero-crossing image. (p585 the third version

has no information )

(1) Edges in the zero-crossing image are thinner than the gradient edges.