Image Processing with MATLAB and AI

Abb. 1: Signalverarbeitung mit MATLAB^® und Künstlicher Intelligenz

Autor:	Ajay Paul
Art:	bachelor thesis
Starttermin:	TBD
Abgabetermin:	TBD
Betreuer:	Prof. Dr.-Ing. Schneider
Zweitprüfer:	Mirek Göbel

Introduction

Signal processing has long been a basis in the analysis and manipulation of data in various domains such as telecommunications, radar, audio processing, and imaging. Signal processing has traditionally focused on analyzing, filtering, and interpreting signals in both the time and frequency domains. With the integration of AI, especially deep learning, the possibilities expand to include noise reduction and more. It is essential in many modern applications such as communications, audio and image processing, biomedical signal analysis, and control systems.

Task list

1. Solve the Image Processing Tasks with classic algorithms.
2. Research on AI Solutions.
3. Evaluation of the solutions using a morphological box (Zwicky box)
4. Solve the Image Processing Tasks with AI algorithms.
5. Compare the different approaches according to scientific criteria
6. Scientific documentation

Getting startes

• You are invited to the image processing class in MATLAB Grader.
• Choose the examples from the categories in table 1. Start with 1 end with 6.
• Solve the tasks with classic algorithms.
• Solve the tasks with AI.
• Save your results in SVN.
• Use MATLAB R2025b for the algorithms.

Image Processing Tasks with classic algorithms

Image Processing: Recovery and restoration of information

Table 1: Image Processing Categories

#	Categorie	Grader Lecture
1	Recovery and restoration of information	5
2	Image enhancement	6
3	Noise Reduction	7
4	Data based segmentation	8
5	Model based segmentation	9
6	Classification	10