Implement Image Compression Using MATLAB in DIP | Image Compression | MATLAB | DIP #imagecompression

Implement Image Compression in Digital Image Processing Using MATLAB:
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✓Implement Image Compression Using Matlab by SVD

✓ In this video, we dive into the fascinating world of image compression using Singular Value Decomposition (SVD) in MATLAB. SVD is one of the most effective techniques for compressing images by reducing their dimensionality while maintaining visual quality. We'll walk through the process step-by-step, from explaining the mathematical concept of SVD to coding the implementation in MATLAB.

📌 What you'll learn:

How Singular Value Decomposition (SVD) works in image processing.

Step-by-step guide on implementing image compression using SVD in MATLAB.

How to adjust the compression ratio and visualize the results.

Practical applications of SVD in data compression and machine learning.
🔧 Topics covered:

Introduction to SVD and its role in image compression.

Writing MATLAB code for image compression.

Running simulations and visualizing the compressed images.

Tips for improving compression efficiency.
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Time Stamps ✨

0:00 Introduction
0:19 Open Matlab
0:33 Compress Image
0:55 Gray Image
1:15 Vector
1:53 SVD
2:34 uint8
3:55 Transpose
4:26 Figure
4:46 Output
5:02 No Figure
5:21 Compression Value
5:53 Conclusion
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