Starosolski Roman
Institute of Informatics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland.
PLoS One. 2016 Dec 22;11(12):e0168704. doi: 10.1371/journal.pone.0168704. eCollection 2016.
In order to improve bitrates of lossless JPEG 2000, we propose to modify the discrete wavelet transform (DWT) by skipping selected steps of its computation. We employ a heuristic to construct the skipped steps DWT (SS-DWT) in an image-adaptive way and define fixed SS-DWT variants. For a large and diverse set of images, we find that SS-DWT significantly improves bitrates of non-photographic images. From a practical standpoint, the most interesting results are obtained by applying entropy estimation of coding effects for selecting among the fixed SS-DWT variants. This way we get the compression scheme that, as opposed to the general SS-DWT case, is compliant with the JPEG 2000 part 2 standard. It provides average bitrate improvement of roughly 5% for the entire test-set, whereas the overall compression time becomes only 3% greater than that of the unmodified JPEG 2000. Bitrates of photographic and non-photographic images are improved by roughly 0.5% and 14%, respectively. At a significantly increased cost of exploiting a heuristic, selecting the steps to be skipped based on the actual bitrate instead of an estimated one, and by applying reversible denoising and lifting steps to SS-DWT, we have attained greater bitrate improvements of up to about 17.5% for non-photographic images.
为了提高无损JPEG 2000的比特率，我们建议通过跳过离散小波变换（DWT）计算的某些选定步骤来对其进行修改。我们采用一种启发式方法以图像自适应的方式构建跳过步骤离散小波变换（SS-DWT），并定义固定的SS-DWT变体。对于大量不同的图像，我们发现SS-DWT能显著提高非摄影图像的比特率。从实际角度来看，通过应用编码效果的熵估计在固定的SS-DWT变体中进行选择可获得最有趣的结果。通过这种方式，我们得到了一种压缩方案，与一般的SS-DWT情况不同，它符合JPEG 2000第2部分标准。对于整个测试集，它的平均比特率提高了约5%，而总体压缩时间仅比未修改的JPEG 2000增加了3%。摄影图像和非摄影图像的比特率分别提高了约0.5%和14%。在显著增加利用启发式方法成本的情况下，基于实际比特率而非估计比特率选择要跳过的步骤，并对SS-DWT应用可逆去噪和提升步骤，我们使非摄影图像的比特率提高了高达约17.5%。
