An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.

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Deep Learning ImageCompressionSimulation
Overview

ImageCompressionSimulation

An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects of different compression algorithms.

Author's Note

This work done behind this program was to investigate the compression effects of different compression algorithms on an real science image which then has over 10000 simulated copies (due to the lack of real data) of it via Monte Carlo methods. These simulated images are then analyzed by Source Extractor- https://sextractor.readthedocs.io/. to examine the pre and post compressive effects on the image.

To be quite honest, this program will probably be outdated and non-functioning by the time someone gets around ACTUALLY trying to run it... The main purpose is to look at legacy code so that I can implement the simulation feature into my other open source project MagnaPY- www.github.com/parkji30/MagnaPY

Some Cool Results from ICS

Some simulated stars using ICS

another simulated star simulated_star

Analysis showing the compression effects of the HCOMPRESS algorithm. We see that the distribution of the ellipticity value detected by source extractor did not get distorted from our Monte Carlo simulation of over 1000 simulated stars as shown above. We conclude that the HCOMPRESS algorithm can be safely used for sources of this nature in our science data.

analysis

Signal to noise plot showing the limitations of Source Extractor. Essentially Source Extractor cannot detect sources with a FWHM less than 1.5 sigma.

signaltonoise

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