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长春光学精密机械与物... [1]
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会议论文 [1]
发表日期
2012 [1]
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Image coding using wavelet-based compressive sampling (EI CONFERENCE)
会议论文
2012 5th International Symposium on Computational Intelligence and Design, ISCID 2012, October 28, 2012 - October 29, 2012, Hangzhou, China
Jin L.
;
Li J.
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提交时间:2013/03/25
In this paper
we proposed a novel coding scheme is proposed using wavelet-based CS framework for nature image. First
two-dimension discrete wavelet transform (DWT) is applied to a nature image for sparse representation. After multi-scale DWT
the low-frequency sub-band and high-frequency sub-bands are re-sampled separately. According to the statistical dependences among DWT coefficients
we allocate different measurements to low- and high-frequency component. Then
the measurements samples can be quantized. The quantize samples are entropy coded and forward correct coding (FEC). Finally
the compressed streams are transmitted. At the decoder
one can simply reconstruct the image via l1 minimization. Experimental results show that the proposed wavelet-based CS scheme achieves better compression performance against the relevant existing solutions.
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