Publication: Noise level reduction of 2d digital signal using toboggan method
| datacite.subject.fos | oecd::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering | |
| dc.contributor.author | Sharon Lim, Su Yin | |
| dc.date.accessioned | 2024-06-12T09:24:11Z | |
| dc.date.available | 2024-06-12T09:24:11Z | |
| dc.date.issued | 2006-05-01 | |
| dc.description.abstract | In this new era, images for the broadcast television, video, camera, remote sensing, medical imaging, machine vision and others sources always contaminate with impulse noise and Gaussian noise. Those image contaminated by noise are uncomfortable for viewing, thus image processing is introduce to tackle this problem. By that, the objective of this project is to achieve image contrast enhancement which implemented by using C++ programming as the user interface (UI). In fact, those noises in the two dimensional images can be reduced by using mean filter, median filter and Gaussian filter. After smoothing those images, we must sharpen those blurry images by using first derivative filter with gradient operators to preserve the edge characteristics. We can integrate both of these filters by using Toboggan method which also defined as downhill method. Those sharp and clear images produced after processing with Toboggan enhancement method in my project is similar as proven by image processing theory. After that, results after using those filters are compared and analyzed by using software like Matlab version 7.0. However, improvement on reducing Gaussian noise with higher value for sigma in images was done, besides filters for improving images which contaminated with both impulse noise and Gaussian noise was also implemented. Eventually, a less noise and clearer output image which had met the objective of this project was successfully produced. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/19447 | |
| dc.language.iso | en | |
| dc.title | Noise level reduction of 2d digital signal using toboggan method | |
| dc.type | Resource Types::text::report | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |