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Introduction:

Image compression is a crucial aspect of modern technology as it allows for the efficient storage and transmission of digital images. With the increasing use of images in various applications such as social media, websites, and medical imaging, the need for effective image compression techniques has become more important than ever. The goal of image compression is to reduce the size of an image file while maintaining its visual quality, thus saving storage space and bandwidth.

This thesis focuses on the study of image compression techniques for efficient storage. The research will explore different compression algorithms and methodologies, their advantages and limitations, and their suitability for various types of images. The ultimate objective is to develop a better understanding of image compression and to propose new techniques that can improve the storage efficiency of digital images.

Chapter 1: Overview
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Introduction to image compression
2.2 Lossless vs. lossy compression
2.3 Types of compression algorithms
2.4 JPEG compression
2.5 PNG compression
2.6 JPEG2000 compression
2.7 Transform coding
2.8 Wavelet-based compression
2.9 Neural network-based compression
2.10 Comparison of compression techniques

Chapter 3: System Design and Methodology
3.1 Introduction
3.2 Data collection and preprocessing
3.3 Selection of compression algorithms
3.4 Implementation of compression techniques
3.5 Evaluation criteria
3.6 Performance metrics
3.7 Experimental design
3.8 Data analysis

Chapter 4: System Implementation
4.1 Introduction
4.2 Implementation of selected compression algorithms
4.3 Testing and evaluation
4.4 Results and discussion
4.5 Comparison with existing techniques
4.6 Optimization techniques
4.7 Future research directions
4.8 Validation of results

Chapter 5: Conclusion and Summary
5.1 Summary of findings
5.2 Contribution to the field
5.3 Recommendations for future research
5.4 Conclusion

Thesis Overview:

Image compression is a fundamental aspect of digital image processing that plays a crucial role in efficient storage and transmission of images. This thesis focuses on exploring various image compression techniques and algorithms to improve storage efficiency while maintaining visual quality. Chapter 1 provides an overview of the study, including the background, problem statement, objectives, limitations, scope, significance, structure, and definition of terms. Chapter 2 presents a comprehensive literature review on different compression algorithms such as JPEG, PNG, JPEG2000, transform coding, wavelet-based compression, and neural network-based compression. Chapter 3 discusses the system design and methodology, including data collection, preprocessing, compression algorithm selection, implementation, evaluation criteria, performance metrics, and experimental design. Chapter 4 elaborates on the system implementation, including testing, evaluation, results, discussion, comparisons, optimization techniques, and future research directions. Chapter 5 concludes the thesis by summarizing the findings, contributions, recommendations for future research, and overall conclusion on image compression for efficient storage.

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