DIP Assignment 4 Computer Science, Assignments of Digital Image Processing

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Muhammad Sohaib
18-Arid-570
BSCS-7B
Assignment 4 of DIP
Q.1 What is the difference between Image Restoration and Image
Enhancement? Describe any three restoration filters.
Answer:
Image Enhancement Image Restoration
1
.
As the name suggests, in Image
Enhancement, the original image is processed
so that the resultant image is more suitable
than the original for specific applications.
The aim of image restoration is to bring
the image towards what it would have
been if it had been recorded without
degradation.
2
.
Image enhancement makes a picture look
better, without regard to how it really truly
should look.
Image restoration tries to fix the image
to get back to the real, true image.
3
.
Image enhancement means improving the
image to show some hidden details.
Image restoration means improving the
image to match the original image.
4
.
Image enhancement is a purely subjective
processing technique.
Image restoration is an objective
process.
5
.
Image enhancement is a cosmetic procedure
i.e. it does not add any extra information to the
original image. It merely improves the
subjective quality of the images by work in with
Restoration tries to reconstruct by using
a priori knowledge of the degradation
phenomena. Restoration hence deals
with getting an optimal estimate of the
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Muhammad Sohaib

18-Arid-

BSCS-7B

Assignment 4 of DIP

Q.1 What is the difference between Image Restoration and Image

Enhancement? Describe any three restoration filters.

Answer:

Image Enhancement Image Restoration 1 . As the name suggests, in Image Enhancement, the original image is processed so that the resultant image is more suitable than the original for specific applications. The aim of image restoration is to bring the image towards what it would have been if it had been recorded without degradation. 2 . Image enhancement makes a picture look better, without regard to how it really truly should look. Image restoration tries to fix the image to get back to the real, true image. 3 . Image enhancement means improving the image to show some hidden details. Image restoration means improving the image to match the original image. 4 . Image enhancement is a purely subjective processing technique. Image restoration is an objective process. 5 . Image enhancement is a cosmetic procedure i.e. it does not add any extra information to the original image. It merely improves the subjective quality of the images by work in with Restoration tries to reconstruct by using a priori knowledge of the degradation phenomena. Restoration hence deals with getting an optimal estimate of the

Image Enhancement Image Restoration the existing data. desired result

Restoration Filters are the type of filters that are used for operation of noisy

image and estimating the clean and original image. It may consist of processes

that are used for blurring or the reverse processes that are used for inverse of

blur. Filter used in restoration is different from the filter used in enhancement

process.

Types of Restoration Filters:

There are three types of Restoration Filters: Inverse Filter, Pseudo Inverse

Filter, and Wiener Filter. These are explained as following below.

1. Inverse Filter:

Inverse Filtering is the process of receiving the input of a system from its output.

It is the simplest approach to restore the original image once the degradation

function is known.

It can be define as:

H'(u, v) = 1 / H (u, v)

2. Pseudo Inverse Filter:

Pseudo inverse filter is the modified version of the inverse filter and stabilized

inverse filter. Pseudo inverse filtering gives more better result than inverse

filtering but both inverse and pseudo inverse are sensitive to noise.

Pseudo inverse filtering is defined as:

H'(u, v) = 1/H (u, v), H (u, v)! = H'(u, v) = 0, otherwise

3. Wiener Filter:

(Minimum Mean Square Error Filter). Wiener filter executes and optimal tradeoff

between filtering and noise smoothing. IT removes the addition noise and inputs

in the blurring simultaneously. Weiner filter is real and even.

It minimizes the overall mean square error by:

Explanation:

1. Read a RGB image using ‘imread’ function.

2. Each RGB component will be in the range of [0 255]. Represent the image in

[0 1] range by dividing the image by 255.

3. Find the theta value. If B<=G then H= theta. If B>G then H= 360-theta

4. Use ‘acosd’ function to find inverse cosine and obtain the result in degrees.

5. Divide the hue component by 360 to represent in the range [0 1]

6. Similarly, find the saturation and the intensity components.

7. Display the image.

Matrix Notation Form:

Q.3 Define and explain

a) Opening and Closing

b) Smoothing and sharpening

c) Boundary extraction

with respect to morphological image processing

Erosion:

 Does the structuring element fit the set?

 Erosion of a set A by structuring element B: all z in A such that B is in A when

origin of B=z

 Shrink the object