The document presents a case study on image restoration, detailing its definition, causes of image degradation, and types of noise impacting image quality. It outlines the significance of image restoration techniques across various fields such as medical imaging and digital photography. Key aspects include the effects of motion blur, poor focus, sensor noise, and different noise types like quantization and salt and pepper noise.

1. IMAGE RESTORATION
PRESENTATION BY MOSTAFA TFAILY
TO DR BILAL GHAZAL
-Case Study

2. OBJECTIVES
• What is Image Restoration?.
• Causes of Image Degradation.
• Types of Noise and Their Characteristics.
• Image Restoration Techniques.
• Applications of Digital Image Processing.

3. WHAT IS IMAGE RESTORTION
Image Restoration is a process in which techniques are used to recover an original image that has been
degraded by various factors.
Various factors may include sensor noise,motion blur, defocus,transmission errors.
Image Restoration is used in NUMEROUS fields including medical imaging,satellite imagery,digital
photography.
Almost Similar to Image Enhancement,but more objective.

4. WHAT IS IMAGE RESTORTION

5. CAUSES OF IMAGE DEGRADATION
• MotionBlur:Movement during image capture can result in blurred images, particularly in low shutter speed conditions or when capturing fast-
moving subjects.
• PoorFocus:Incorrect focus settings or focusing errors can lead to blurry images or misfocused areas.
•
.
Imagedegradationcanoccurdueto variousfactors,bothduringcaptureandprocessing. Hereare somecommon
causes:
SensorNoise:Noise generated by the camera sensor or electronic components can degrade image quality, especially in low-light
conditions.

6. EXAMPLE OF IMAGE DEGRADATION
Motion Blur Poor Focus

7. types of noise and their characteristics
• NOISE REFERS TO ANY UNWANTED OR IRRELEVANT DISTURBANCETHAT INTERFERES WITH THE CLARITY OR
FIDELITY OF A DESIRED SIGNAL,HERE ARE SOME TYPE OF NOISES:
Quantization Noise: Imagine you have a digital signal that looks like a staircase, with flat steps instead of a smooth curve. These flat steps
are what we call quantization noise.
salt and Pepper Noise: Imagine you have a picture that looks like it has random black and white specks all over it, like salt and
pepper. These specks are what we call salt and pepper noise. It's often caused by errors in the image acquisition process, and can
make it difficult to see the actual image

8. Example Of Noises
Salt and
pepper
noise
Quantization
noise

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11. INVENTION DESIGN PROCESS
• Talk about the design process
• Did your first build work, or did
you have to change your ideas?
Why?
• Did you have to change the
materials you used as you tested
your invention? Why?
<Insert pictures or drawings of your invention design/building process>
*you can insert a new slide for these pictures/drawings if you need to!

12. MY INVENTION IN USE!
Talk about how people reacted to your invention
• Did it solve the problem/need you identified?
• Did it work as planned? Did it help whom it needed to help?
<Insert pictures or drawings of your invention being
used, with a description entered here>
*you can insert a new slide for these pictures/drawings if
you need to!
<Insert pictures or drawings of your invention being
used, with a description entered here>
*you can insert a new slide for these pictures/drawings if
you need to!
<Insert pictures or drawings of your invention being
used, with a description entered here>
*you can insert a new slide for these pictures/drawings if
you need to!

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