Home > Search Results: keywords:"signal border extension"
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Segmented wavelet transform of images
 Kučera, Michal ; Rajmic, Pavel (referee) ; Průša, Zdeněk (advisor)
This master’s thesis is dealing with modification of classical discrete time wavelet transform algorithm to be able to split input image into several segments which could be independently processed. Segmented discrete time wavelet transform is introduced and implemented and the tests shows that it produces the similar values of wavelet coefficients as the classical approach. Complete independent image segment processing is allowed thanks to inverse segmented discrete time wavelet transform. It’s obvious that redundancy calculations appear when the image is processed segment by segment compared to transform the image at once. The redundancy rises with increasing decomposition depth and filter length, however it falls when the segment dimensions are increased. It happens because it is worked with smaller amount of segments which needs to extend. The extension with neighbor samples is the only source of redundancy. The thesis also contains description of two different approaches to signal border extension: firstly complete extension for all decomposition levels before the transformation itself and secondly classical method when the signal is extended in each decomposition step. Both approaches have the same results of image reconstruction, but it distinguishes in calculated wavelet coefficients. Four kinds of signal border extension are compared by using MSE and PSNR. The results of all approaches are similar, however the smooth padding of order 0 and symmetric-padding could be slightly favored against smooth padding of order 1 and zero-padding which shows higher MSE.
Detailed record
Segmented wavelet transform of images
 Kučera, Michal ; Rajmic, Pavel (referee) ; Průša, Zdeněk (advisor)
This master’s thesis is dealing with modification of classical discrete time wavelet transform algorithm to be able to split input image into several segments which could be independently processed. Segmented discrete time wavelet transform is introduced and implemented and the tests shows that it produces the similar values of wavelet coefficients as the classical approach. Complete independent image segment processing is allowed thanks to inverse segmented discrete time wavelet transform. It’s obvious that redundancy calculations appear when the image is processed segment by segment compared to transform the image at once. The redundancy rises with increasing decomposition depth and filter length, however it falls when the segment dimensions are increased. It happens because it is worked with smaller amount of segments which needs to extend. The extension with neighbor samples is the only source of redundancy. The thesis also contains description of two different approaches to signal border extension: firstly complete extension for all decomposition levels before the transformation itself and secondly classical method when the signal is extended in each decomposition step. Both approaches have the same results of image reconstruction, but it distinguishes in calculated wavelet coefficients. Four kinds of signal border extension are compared by using MSE and PSNR. The results of all approaches are similar, however the smooth padding of order 0 and symmetric-padding could be slightly favored against smooth padding of order 1 and zero-padding which shows higher MSE.
Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English