Publication: Design of efficient baseline coders for image compression
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Date
2005-03-01
Authors
Tharmalingam, Vicknatheeban
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Abstract
Image compression is the process of reducing the number of bits required to represent an image. This can be achieved by reducing (or ideally, eliminating) various types of redundancy that exist in the imaging data. This research develops various types of down-sampling filters to compress the image and followed by up-sampling filters to decompress the image. The concept used to down-sample is by deleting either the odd or even numbered columns or rows. Besides that, the columns and rows are also deleted in two’s to further compress the image. The image is then up-sampled by using duplication or replacing the deleted row or columns with the average of other rows or columns. The compression ratio achieved through this research is 50% and 67%. The images are then compared by the Peak Signal-to-Noise Ratio and through observation to decide on the best type of filter. Through the research and results, it is proved that the filter that up-samples the image by replacing the deleted rows with the average of the two subsequent even numbered row has the best output.