Publication:
Two-tone image compression using quad tree structure

datacite.subject.fosoecd::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
dc.contributor.authorTan, Joo Wei
dc.date.accessioned2024-08-01T02:14:55Z
dc.date.available2024-08-01T02:14:55Z
dc.date.issued2009-04-01
dc.description.abstractImage compression is the process of data compression on the digital images. It reduces the number of bits required to represent an image. This can be achieved by reducing various types of redundancy that exist in the imaging data. The objective of this research is to develop and implement the image compression by using the quad-tree structure technique. The concept of Quad-tree Coding is original image recursively subdivided into 4 quadrants or regions until the unit cell pre-setting in program. Every subdivision forms the level information. And the information from each level used to decode to the original image. The quad-tree technique is a type of lossy image compression which means that some data will be changed or loss in reconstruction. The images are then measured by the Compression Ratio (CR) and Peak Signal-to-Noise ratio (PSNR). Through the CR and PSNR, the comparison between the images can be made, how much does the compression work can be measured and shown. The compression which stops breaking image at 4-by-4 pixels has higher compression ratio, i.e. 91.7%, while the compression which stop breaking image at 2-by-2 pixels has lower compression ratio, i.e. 66.9%. But, the higher value of PSNR (more than +10dB) for the compression using 2-by-2 pixels shows that the quality of decompressed image for compression using 2-by-2 pixels is better compare to the compression using 4-by-4 pixels (less than +10dB).
dc.identifier.urihttps://erepo.usm.my/handle/123456789/19961
dc.language.isoen
dc.titleTwo-tone image compression using quad tree structure
dc.typeResource Types::text::report
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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