Proj-2015-2016-Astroimage/Fiche

Subject: Astroimage

Subject summary

This software system will be a Astro Images Processing System for Amateur astronomers. This system will be designed to preprocess and process astronomical images. By maximizing preprocess and process efficiency, the system will meet the customers’ needs while remaining easy to understand and use.

Task team

Supervisors:

• Olivier Richard
• Bruno Bzeznik

Students:

• Quentin GERRY (RICM4)
• Nicolas BLANC (RICM4)
• Coralie RACHEX (RICM4)

Week 1 (January 11th - January 17th)

Objectives

• Choice of the workgroup
• Choice of the subject

Work done

• Workgroup chose
• Selection of project in progress

Problems faced

• Not priority subject
• Few details of the project

Week 2 (January 18th - January 24th)

Objectives

• Defend our project choice
• Contact Bruno Bzeznik for more details
• Inquire about the techniques of astronomical image processings and about the existing software

Work done

• Confirmation of the project choice.
• Searches on the image processing.

Problems faced

• The meeting with Bruno Bzeznik is scheduled for the next week. Having only little information on the project, we can't really progress.
• We find little information about the astronomical image processing and we haven't a lot of details to direct our searches.

Week 3 (January 25th - January 31st)

Objectives

• We need to get more information concerning the project, to be able to begin to think about its implementation.

Work done

• SRS: Project requirements (SRS)

Problems faced

• The astronomical image processing in python seems much more complicated than in other language (reading of a .RAW image in particular).
• This project seems to be very long to realize and we have to make choice about the priority functions of software.

Week 4 (February 1st - February 7th)

Objectives

Researching :

• The .FITS file format
• The .RAW file format
• Library python about the astronomical images processing or the images processing
• Python
• Algorithms about astronomical image processings

Work done

• UML: Use Case, Sequence and state diagrams.

Problems faced

• Books about the astronomical image processing which we found speak only about the use of the existing software. It's difficult to find algorithms for the astronomical images processing.
• Library Python aren't adapted to our needs. So, we must start from scratch.

Week 5 (February 8th - February 14th)

Objectives

• We have to continue our search and begin to code the functions allowing to process the RAW images and FITS

Work done

• Design patterns
• Functions allowing to treat the images .RAW and .FITS

Week 6 (February 15th - February 21st)

Objectives

• We have to continue our search and begin to code the image processing functions

Work done

Image processing functions :

• Saturation
• Contrast
• Denoising

Week 7 (February 29th - March 6th)

Objectives

• We have to continue our search and begin to code the astronomical image processing functions

Work done

Astronomical image processing functions :

• MasterBias
• MasterDark
• MasterFlat