Denoising histological images for a better colour image segmentation / Sulastri Putit

De-noising can be generally defined as removing noise in image. According to (Pierrick Coupe et.al, 2008), image de-noising is used to improve the accuracy of various image processing algorithms such as registration or segmentation. Generally, the quality of the artifact correction influences perfor...

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Bibliographic Details
Main Author:	Putit, Sulastri
Format:	Thesis
Language:	English
Published:	2013
Subjects:	RB Pathology Radiography
Online Access:	https://ir.uitm.edu.my/id/eprint/87238/1/87238.pdf
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id	my-uitm-ir.87238
record_format	uketd_dc
spelling	my-uitm-ir.872382024-02-24T17:43:14Z Denoising histological images for a better colour image segmentation / Sulastri Putit 2013 Putit, Sulastri RB Pathology Radiography De-noising can be generally defined as removing noise in image. According to (Pierrick Coupe et.al, 2008), image de-noising is used to improve the accuracy of various image processing algorithms such as registration or segmentation. Generally, the quality of the artifact correction influences performance of the image processing procedure. So, the noise removal aims at improving the image quality for visual inspection. The preservation of relevant image information is important especially in medical context. The problem statements of the study have been defined as the problem of noise, the problem of colour image segmentation and the problem of conventional method in preparing histological images for analysis. In order to achieve better colour for image segmentation, the objectives of the study have to fulfill first which is to perform de-noising on colour histological images, then to perform colour image segmentation on histological images and finally to evaluate the effect of denoising on colour image segmentation. In this study, the de-noising concept for colour image preprocessing and segmentation are proposed since these two processes has been widely accepted as an important component of the image mining in order to enhance the images. 2013 Thesis https://ir.uitm.edu.my/id/eprint/87238/ https://ir.uitm.edu.my/id/eprint/87238/1/87238.pdf text en public masters Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Jamil, Nursuriati
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Jamil, Nursuriati
topic	RB Pathology Radiography
spellingShingle	RB Pathology Radiography Putit, Sulastri Denoising histological images for a better colour image segmentation / Sulastri Putit
description	De-noising can be generally defined as removing noise in image. According to (Pierrick Coupe et.al, 2008), image de-noising is used to improve the accuracy of various image processing algorithms such as registration or segmentation. Generally, the quality of the artifact correction influences performance of the image processing procedure. So, the noise removal aims at improving the image quality for visual inspection. The preservation of relevant image information is important especially in medical context. The problem statements of the study have been defined as the problem of noise, the problem of colour image segmentation and the problem of conventional method in preparing histological images for analysis. In order to achieve better colour for image segmentation, the objectives of the study have to fulfill first which is to perform de-noising on colour histological images, then to perform colour image segmentation on histological images and finally to evaluate the effect of denoising on colour image segmentation. In this study, the de-noising concept for colour image preprocessing and segmentation are proposed since these two processes has been widely accepted as an important component of the image mining in order to enhance the images.
format	Thesis
qualification_level	Master's degree
author	Putit, Sulastri
author_facet	Putit, Sulastri
author_sort	Putit, Sulastri
title	Denoising histological images for a better colour image segmentation / Sulastri Putit
title_short	Denoising histological images for a better colour image segmentation / Sulastri Putit
title_full	Denoising histological images for a better colour image segmentation / Sulastri Putit
title_fullStr	Denoising histological images for a better colour image segmentation / Sulastri Putit
title_full_unstemmed	Denoising histological images for a better colour image segmentation / Sulastri Putit
title_sort	denoising histological images for a better colour image segmentation / sulastri putit
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/87238/1/87238.pdf
_version_	1794192123177730048

Denoising histological images for a better colour image segmentation / Sulastri Putit

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