数字图像处理(双语)期中考试试卷答案

考试试卷(答案)

试卷编号：( )卷课程编号：课程名称：数字图像处理（双语）考试形式：

适用班级：姓名：学号：班级：

学院：信息工程学院专业：电子系各专业考试日期：

一二三四五六七八九十总分累分人

签名题分20 20 20 20 20 0 0 0 0 0 100

得分

考生注意事项：1、本试卷共5页，请查看试卷中是否有缺页或破损。如有立即举手报告以便更换。

2、考试结束后，考生不得将试卷、答题纸和草稿纸带出考场。

一、基础知识填空题(1,2为单项选择,每空3分,3,4为多项选择,每空2分,共20分),

1 1、When you enter a dark room on a bright day, it takes some time to see well

enough, this is the visual process or visual phenomenon of

A. (Brightness adaptation.)

B. (Brightness discrimination.)

C. (Optical illusion.)

D. (Simultaneous contrast.)

2、The visible spectrum consists of electromagnetic spectrum nearly in the

range of wavelength:

A. (10 – 400 nm)

B. (0.01 – 10 nm)

C. (400 – 700 nm)

D. (700 – 1500 nm)

3、For V = {1}, the subsets S1 and S2are

A. (m-connected)

B. (8-connected )

C. (4-connected)

D. (None of these 3)

4、Two pixels p and q are at the locations shown in the figure, their Euclidean,

city-block and chessboard distances are respectively:

A. D e= ( )

B. D4 = ( 6 )

C. D8 = ( 4 ) 0 0 0 1 2

1 2 7 6 5(p)

3 4 5 6 7

(q) 4 5 6 7 3 得分评阅人

二、空域图像增强题1(Image enhancement in the spatial domain) (20分) Exponential of the form s = T (r ) = 2552

r e α-, 0 ≤ r ≤ 255, with α being a positive constant, are useful for constructing smooth gray-level transformation functions. (1) Start with this basic function and construct transformation functions having the shapes shown in the above figures. (15分) (2) What kind of transformation does the function of (a) approximately

complete for an input of a gray intensity image? （5分） (1) (a)

so

.

(b)

so

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255 255

255 (b)

(a)

(c)

三、空域图像增强题2(Image enhancement in the spatial domain) (20分)

The White bars in the test pattern shown are 7 pixels wide and 210 pixels high. The separator between bars is 17 pixels. What would this image look like after application of

1. A 3×3 median filter?

2. A 7×7 median filter?

3. A 9×9 median filter?

4. A 15×15 median filter?

( Note: in your answer, quantitative analysis is expected. )

Answer:

The separator between bars is 17 pixels wide > 15, so none of the 4 filters can remove any black pixels. We can treat all black pixels as background.

1. Applying a 3×3 median filter removes the 1 pixel at the top left, top right, bottom left and bottom right locations of each bar, as shown in (a), which is an amplified corner of the filtered

image.

2. Applying a 7×7 median filter remove 6 pixels located at the top left, the top right, the bottom left, the bottom right of each bar, as shown in (b)，which is an amplified corner of the median filtered image.

0111110 0001000 3×3 1111111 7×7 01111110 1111111 01111110

3. Applying a 9×9 median filter remove 10 pixels located at the top left, the top right, the bottom left, the bottom right of each bar, as shown in (c). which is an amplified corner of the median filtered image 0000000 9×9 0011100

0111110

4. This time all bars are disappeared.

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(a)

(b)

(a)