Lossy Image Compression Using Multi Scale Decomposition Coding Schemes
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The increased use of computer and internet had been associated with the wide use of image data. This huge quantity of data can lead to many difficulties frequently, it must be stored, retrieved, analyzed and processed in an effective manner. Considerable storage capacity and very high bandwidth are required to transfer uncompressed multimedia (image, video and audio) data. So, the need of compressing image is raised dramatically. Despite a significant development in the performance of compression techniques, there is still room for new compression techniques. In this book, two coding schemes h...
The increased use of computer and internet had been associated with the wide use of image data. This huge quantity of data can lead to many difficulties frequently, it must be stored, retrieved, analyzed and processed in an effective manner. Considerable storage capacity and very high bandwidth are required to transfer uncompressed multimedia (image, video and audio) data. So, the need of compressing image is raised dramatically. Despite a significant development in the performance of compression techniques, there is still room for new compression techniques. In this book, two coding schemes have been developed for compressing still images (smoothed and sharp edge) images based on wavelet transform coding and two types of 3 Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI) and linear polynomial approximation) to doubly prune the existing smoothing parts of the image signal to achieve significant reduction in image data size without making significant subjective distortions. Where the image size, bit depth, and block size are different.
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