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)

= Progress of the project =

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

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.

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.

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

 * [[Media:AstroImage-UML.pdf | 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.

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

Problems faced

 * We don't have time to create a function of debayeurisation, we have to use the "rawpy" library even if it affects the images quality.
 * FITS is often used for the images in black and white and not for color images. It's difficult to find relevant information on this matter.

Objectives

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

Work done
Image processing functions :
 * Saturation
 * Contrast
 * Denoising

Problems faced

 * There are many different algorithms, we have to make a choice according to the ease of implementation and the efficiency of each.

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

Problems faced

 * These algorithms are difficult to verify (effects are little visible and the processing time is long)