Some Case Studies on Signal, Audio and Image Processing Using Matlab E-Book

Dr. Hedaya Mahmood Alasooly

• Herausgeber: BookRix
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch
• Veröffentlichungsjahr: 2020

Beschreibung

This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts. Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter. Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands. Then the discrete cosine transform compression examined on the audio signal  at different compression rates: 50%, 75% , 87.5%   Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness                  

Leseprobe

Dr. Hedaya Mahmood Alasooly

Some Case Studies on Signal, Audio and Image Processing Using Matlab

BookRix GmbH & Co. KG80331 Munich

Some Case Studies on Signal, Audio and Image Processing Using Matlab

Some Case Studies on Signal, Audio and Image Processing Using Matlab

By

Dr. Hedaya Mahmood Alasooly

Some Case Studies on Signal, Audio and Image Processing Using Matlab

Supervised By

Dr. Hedaya Mahmood Alasooly

Diploma Project

Done by:

20073986: Mohameed Abdl Elah

20072601: Khalil Ebrahim Ahmed

20070618: Hasan Makki Mahdi

20073359: Ameen Ebrahim Ahmed

Abstract

This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts.

Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter.

Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands. Then the discrete cosine transform compression examined on the audio signal at different compression rates: 50%, 75% , 87.5%

Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness

Table of Contents

Table of Contents

1. Introduction

2. Theory Related To Project

2.1 What is the signal Processing Toolbox in Matlab

2.2 Signal and Linear System Models

2.3 Filter Implementation and Analysis

2.4 Digital Filter Design Methods

2.5 Transforms

2.6 Frequency Response

2.7 GUIs for Filter Design, Analysis, and Visualization……………18

3. Descrption of Project and Results and Analysis

3.1 Part I: Design different filters for filtering sinusoidal signal

3.2 Part II: Audio Processing

3.2.2 Audio Compressing

3.3 Part III: Image Processing

3.3.1 Filtering

3.3.2 Other operations: Image cropping, sizing and histogram equalization, changing brightness

4. Conclusion

5. References

1. Introduction:

1. Introduction:

This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts

Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter.

Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands:

Then the discrete cosine transform compression examined on the audio signal at different compression rates: 50%, 75% , 87.5%

Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness.