Abstract
In this paper, a novel image compression approach for low-bit-rate applications is proposed. Our algorithm combines both super-resolution techniques and compression techniques so that a higher compression rate, with satisfactory visual quality, can be achieved. In the coding process, the down-scaled version of the input image is divided into blocks, and each block is classified as either a textural block or a flat block. For the flat blocks, a skipping scheme is employed in the compression process so as to save the bits. The coding of the skip blocks, identified by the skipping scheme, will make reference to the reconstructed regions of the image in the encoding process. For the textural blocks, the standard JPEG coding method is employed. In the decoding process, the decompressed image is up-scaled using a super-resolution algorithm. Experimental results show the superior performance of our method in terms of both compression efficiency and visual quality.
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Xia, Q., Li, X., Zhuo, L., Lam, K.M. (2010). A Novel Low-Bit-Rate Image Compression Algorithm. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15696-0_10
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DOI: https://doi.org/10.1007/978-3-642-15696-0_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15695-3
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