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1. Optimizing
Image
Compression: A
MATLAB
Approach
for Lossless
Compression

2. Guided by – Dr.
Lokesh Sharma
Presented by -
1.Kamlesh Pawar (202201070138)
2.Omkar Varote (202201070136)

3. Introduction
In this presentation, we will explore optimizing
image compression using . We will focus
on lossless compression techniques and their
applications in image processing.

4. What is lossless image
compression?
Lossless image compression
is a method of reducing the
size of an image file without
losing any information or
visual quality. The goal of
lossless compression is to
compress the data in such a
way that the original image
can be perfectly
reconstructed from the
compressed version.

5. Why we Requires lossless image
compression/application ?
1.Professional Imaging and Photography-
2. Medical Imaging
3. Scientific and Research Applications
4. Legal and Forensic Imaging
5. Graphics and Design

6. Why we requires
matlab ?
MATLAB offers powerful tools
for image compression. It
provides a range of built-in
functions and tools that make it
convenient for implementing and
experimenting with various image
processing and compression
techniques, including lossless
image compression.

7. Importance of Lossless
Compression Evaluation
Evaluating the effectiveness of lossless
compression is essential. We will discuss metrics
such as compression ratio, peak signal-to-noise
ratio (PSNR),and structural similarity index
(SSIM).

9. Advanced of lossless
image compression
Exploring advanced techniques for
image compression is crucial for
achieving optimal results.We will
cover dictionary-based compression,
fractal compression, and wavelet-
based compression.

10. Conclusion
Lossless image compression using MATLAB provides
efficient techniques for reducing the size of digital images
while preserving all the original data.

11. Thank
You !