When using digital images or video, the amount of storage space or transmission bandwidth required can be quite large when the media is in its raw form. Recently, there has been a dramatic increase in the usage of these digital media types. Consequently, there has also been an increase in the research devoted to reduce the data required to represent these types of digital signals. In this thesis, a study is presented of a method that uses adaptive sampling and interpolation for image and video data compression. A recursive splitting method that creates an adaptive sampling grid, is described, along with a discussion concerning the interpolation of these samples for the reconstruction of the original image or video. Implementation and optimization issues concerning the presented image and video data compression algorithms are discussed. Examples showing the effects of these methods are given and compared to existing standard data compression techniques.
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