# Digital Image Processing (4 projects)

Project 1:

Zooming and Shrinking Images

Assume that the desired zoom/shrink factors are integers, zoom and shrinking the

1) by Pixel Replication

(a) Write a computer program capable of zooming and shrinking an image by pixel

replication.

(b) Use your program to shrink the original image by a factor of 10.

(c) Use your program to zoom the image in (b) back to the resolution of the

original.

Explain the reasons for their differences.

2) by Bilinear Interpolation

(a) Write a computer program capable of zooming and shrinking an image by

bilinear interpolation. The input to your program is the desired resolution (in dpi) of

the resulting image.

(b) Use your program to shrink the following image from 1250 dpi t0 100 dpi.

(c) Use your program to zoom the image in (b) back to 1250 dpi.

Explain the reasons for their differences.

----

Project 2:

Image Enhancement Using Intensity Transformations

The focus of this project is to experiment with intensity transformations to enhance

using

(a) The log transformation shown in Chapter 3.

(b) A power-law transformation of the form shown in Chapter 3.

In (a) the only free parameter is c, but in (b) there are two parameters, c and r for

which values have to be selected. As in most enhancement tasks, experimentation

is a must. The objective of this project is to obtain the best visual enhancement

possible with the methods in (a) and (b). Once (according to your judgment) you

have the best visual result for each transformation, explain the reasons for the

major differences between them.

----

Project 3:

Histogram Equalization and Matching

equalization on it.

(a) Write a computer program for computing the histogram of an image.

(b) Implement the histogram equalization technique discussed in Section 3.3.1.

(c) Implement the histogram matching discussed in Section 3.3.2.

Note that your report should include the original image, a plot of its histogram, a

plot of the histogram-equalization transformation function, a plot of the

histogram-matching transformation function, the enhanced image, and a plot of its

histogram. Use these information to explain why the resulting image was enhanced

as it was. Comparing with two enhancement method, explain the reasons for their

differences.

----

Project 4:

Image Enhancement by High-Boost Filtering

When the input image is darker than desired, the high-boost filtering can help to

increase in average gray level of the image. Download ‘[login to view URL]’ from the folder of

3

‘projectImages’.

(a) Use the program of spatial filtering to implement high-boost filtering, as given

in Section 3.7.2. The averaging part of the process should be done using the filter

(b) Enhance the testing image using the program you developed in (a). Changing

the parameter A, your objective is to obtain the best result.

----

These 4 projects, I will be providing images needed in these projects.

Skills: C++ Programming, Image Processing

( 0 reviews ) Lahti, Finland

Project ID: #19612962

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ExpertSoul

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