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An Adaptive Image Compression Method Based on Vector Quantization

机译:基于矢量量化的自适应图像压缩方法

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摘要

With the growth of Internet, Image compression has become a popular issue. Since the traditional Vector Quantization (VQ) produces compressed images with a quality at about 27 to 30 dB or so, the techniques of quality improvement is limited. Thus in this paper, we proposed an adaptive image compression method based on VQ, which can adjust the encoding of the difference map between the original image and its restored VQ compressed version. Experimental results show that although our scheme needs to provide extra data, it can substantially improve the quality of VQ compressed images, and further be adjusted depending on the difference map.
机译:随着Internet的发展,图像压缩已成为一个流行的问题。由于传统的矢量量化(VQ)产生的压缩图像的质量约为27到30 dB左右,因此质量改进技术受到限制。因此,在本文中,我们提出了一种基于VQ的自适应图像压缩方法,该方法可以调整原始图像与其恢复的VQ压缩版本之间的差异图编码。实验结果表明,尽管我们的方案需要提供额外的数据,但它可以显着提高VQ压缩图像的质量,并可以根据差异图进行进一步调整。

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