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Adriano Lopez de Onate - BSc in Computer ScienceSupervised by Dr. Amir AtapourDecember the 5th, 2023

Generative modelling for image compression and reconstruction of X-RAY images

THE PIED PIPER ALGORITHM

  • The Pied Piper algorithm from the show Silicon Valley is a video compression software program written in C that achieves a Weissman score in the fives.
  • This type of video compression technology is said to be able to actually shrink the internet by as much as 10 percent with widespread adoption.

JUSTIFICATION AND BACKGROUND: SILICON VALLEY

jUSTIFICATION AND bACKGROUND: COMPRESSION - THE MAGIC KEY TO EVOLUTION

Napster1999

USBs1996

Mobile device2010

DVDs1995

HHDs1980 - 1990

COMPRESSED
Originial
Originial
Originial

LOSSY

LOSSLESS

TWO MAIN TYPES:

DATA COMPRESSION

Data compression is a process of reducing the size of data files or streams by encoding information using fewer bits than the original representation.

jUSTIFICATION AND bACKGROUND: whAT IS dATA COMPRESSION

SIZE: 412KB

SIZE: 798KB

FINAL OUTPUT

INTERMEDIATE

ORIGINAL

SIZE: 1.4Mb

Introduction

  • This project aims to merge the fields of image enhancement and data compression by developing an innovative approach using Generative Networks to achieve adaptive image compression.

PERSONAL PROJECT: AIMS AND SCOPE

PERSONAL PROJECT APPROACH: GAN VS DIFFUSION

VS

Generative Adversarial Models

Generative Adversarial Network (GAN) involves training an encoder and decoder to compress and reconstruct the original images.

DIffusion-Based Models

Diffusion-based models aim to strike a balance between compression and reconstruction fidelity through a diffusion process.

SUPERB!

PERCEPTUALQUALITY

COMPRESSION

PERSONAL PROJECT: FINAL SCOPE

  • Models apart, my project is therefore entirely based on finding the "perfect" matching point between compression and quality using a lossy apporach

PERSONAL PROJECT: work and further work!

4.

3.

2.

1.

Try to beat the current state-of-art!(Perhaps a tad too ambitious)

Train the model on medicals datatset

Evaluate the current research papers

Getting the best out of Diffusion and Adversarial models

- Richard Endricks, Silicon Valley [HBO, 2014]

"Entropy is the silent DJ at the data compression party. It spins the records of disorder, but our algorithms are here to dance with chaos and make sure the beats are still groovy."

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Overview of the architecture. Given an input image x and target rate factor λrate, we obtain a base codec reconstruction x ̃. the DDPM is conditioned on x ̃ and learns to model a reverse diffusion process that generates residuals r0 from sampled gaussian noise latents rT . The enhanced reconstruction xˆ is then obtained by adding the predicted residual to x ̃

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Example of Diffusion-based compression

The entire model is trained in the first stage, and the second stage trains only the decoder.The interpolated decoder reconstructs an input image from quantized latent code. Q, AE, and AD are a quantizer, an arithmetic encoder and an arithmetic decoder, respectively.

Example of GAN-based compression
Data compression is a very niche field!
Papers, papers and papers

DMGANs ?

FINDING THE BEST MATCHING POINT
Generative Model

Size: 457Kb

Size: 1.7Mb

Original
Quantized x
Reconstruction

Decoder

Encoder

OUTPUT (x')
INPUT(x)
EXAMPLE OF GAN-BASED COMPRESSION AT 0.0108 BPP