From 1950215008596faa19358fbfdae1f441533ef070 Mon Sep 17 00:00:00 2001 From: Phuntsok Drak-pa Date: Tue, 27 Nov 2018 14:28:29 +0100 Subject: [PATCH] added files for report, have to work some more on this project --- .gitignore | 9 ++++-- img/asterix.png | Bin 0 -> 374693 bytes rapport.org | 81 ++++++++++++++++++++++++++++++++++++++++++++++++ rapport.pdf | Bin 0 -> 487564 bytes 4 files changed, 87 insertions(+), 3 deletions(-) create mode 100644 img/asterix.png create mode 100644 rapport.org create mode 100644 rapport.pdf diff --git a/.gitignore b/.gitignore index d2a3277..1407b4c 100644 --- a/.gitignore +++ b/.gitignore @@ -1,8 +1,11 @@ +!.gitignore +*.out +*.su +*.tex bin build debug -!.gitignore -*.out +_minted-rapport/ +auto/ \.idea/ cmake-build-debug/ -*.su diff --git a/img/asterix.png b/img/asterix.png new file mode 100644 index 0000000000000000000000000000000000000000..8577cd6f9271d4fe44e79e73b4065ce81e1acbed GIT binary patch literal 374693 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\hypersetup{colorlinks=true,linkbordercolor=red,linkcolor=blue,pdfborderstyle={/S/U/W 1}} +#+OPTIONS: toc:nil +src_latex{\newpage} +#+TOC: headlines +src_latex{\newpage} + +* Le problème + +Le but de ce projet a été de créer un logiciel permettant la compression d’images via la détection de surfaces d’une même couleur, ainsi que de permettre la décompression du fichier ainsi généré à la compression en une image identique à l’image d’origine. Il est à noter que cet algorithme est orienté vers les images de style /comics/ ou avec peu de couleurs, d’où l’image test que vous trouverez en [[*Image de test][annexe]] qui fut mon image de test principale. + +* Résolution initiale du problème + +Afin de résoudre ce problème, je me suis basé sur un algorithme de M. Jean-Jaques Bourdin et l’ai adapté au problème de la manière suivante : pour chaque pixel de l’image, je teste si le pixel courant a une couleur identique à la couleur d’une surface, ou zone, déjà existante. Si une telle zone n’existe pas déjà, alors je la créé puis pour chaque pixel de la ligne courante je me déplace à l’extrême gauche et à l’extrême droite du segment de la même couleur que le pixel courant. Ainsi on obtient un segment de couleur unie, et il est donc possible de maintenant stocker uniquement les limites de ce segment et à l’ajouter à la collection de segments de la zone, qui elle contient les informations de la couleur de la zone. Ensuite, pour chaque pixel en dessus puis en dessous de ce segment, on répète la même procédure. Cela permet de lister toutes les zones contigües et de les ajouter ainsi à la zone courante. + +* Améliorations possibles +** Algorithme +Il est possible d’améliorer l’algorithme par rapport à celui utilisé initialement en ignorant l’étape de test des pixels supérieurs et inférieurs à un segment testé. En effet, cette étape est un résidu de l’algorithem d’origine qui a pour but de ne détecter qu’une zone dont tous les segments sont contigus à au moint un autre segment de la même forme, le tout ne constituant qu’une seule et unique forme continue. Hors ici ce dernier point ne nous intéresse pas, et deux formes de la même couleur n’ont pas à être considérées comme étant deux entités différentes. Ainsi, en ignorant cette étape cela permet de passer de manière itérative sur tous les pixels, simplifiant ainsi l’algorithme. +# TODO: faire cette version de l’algo + +** Sortir du concept d’image avec des lignes et colonnes +L’algorithme actuel considère le fichier d’entrée comme étant une image en deux dimensions, limitant ainsi les segments au début d’une ligne de pixels même si le pixel précédent dans le vecteur dans lequel ces derniers sont stockés est de la même couleur, divisant ainsi des segments en plusieurs segments inutilement. En ignorant ces fins de lignes pour ne procéder qu’à l’analyse des pixels comme ne faisant partie que d’une ligne unique permettrait d’éviter ces ajouts inutiles de segments, et ainsi économiser un peu d’espace avec le fichier compressé. Cependant, je ne pense pas que cette solution soit aussi efficace que la possibilité suivante avec laquelle la possibilité actuelle d’optimisation n’est pas compatible. + +** Espace de stockage +Actuellement, chaque position de pixel est stockée via deux ~uint64_t~ donnant l’extrême gauche et l’extrême droite d’un segment, ainsi stockant le segment individuel sur seize octets. L’emplacement est considéré comme étant l’emplacement sur un vecteur à dimension unique stockant successivement tous les pixels. Il est possible à la place de cette méthode de considérer la dimension duelle de l’image et de ne stocker que la position verticale du segment et ses extrêmes gauche et droit sur un ~uint32_t~. Cela permet donc d’indexer des segments sur des images de 2^{64} pixels (plus de quatre milliards de pixels) de haut et de large, ce qui est largement suffisant pour la majorité des cas, tout en utilisant quatre octets de moins que pour la version actuelle du programme. Il serait également possible de stocker ces valeurs sur trois ~uint16_t~, n’utilisant ainsi que six octets au total et limitant la taille maximale de l’image d’entrée à 2^{16} pixels de haut et de large. + +# TODO : bosser dessus + +* Conclusion + +src_latex{\newpage} +* Annexes +** Image de test + +#+ATTR_LATEX: :width 4.0in +[[./img/asterix.png]] + +src_latex{\newpage} +** Code source + +~main.c~ +#+INCLUDE: ./src/main.c src C -n + +~compress.h~ +#+INCLUDE: ./src/compress.h src C -n + +~compress.c~ +#+INCLUDE: ./src/compress.c src C -n + +~uncompress.h~ +#+INCLUDE: ./src/uncompress.h src C -n + +~uncompress.c~ +#+INCLUDE: ./src/uncompress.c src C -n + +~ppm.h~ +#+INCLUDE: ./src/ppm.h src C -n + +~ppm.c~ +#+INCLUDE: ./src/ppm.c src C -n + +~utilities.h~ +#+INCLUDE: ./src/utilities.h src C -n + +~utilities.c~ +#+INCLUDE: ./src/utilities.c src C -n + +~darray.h~ +#+INCLUDE: ./src/darray.h src C -n + +~darray.c~ +#+INCLUDE: ./src/darray.c src C -n diff --git a/rapport.pdf b/rapport.pdf 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