为满足电能质量监测网存储与传输海量录波数据的需要,提出了提升格式的2维离散小波变换、多级树集合分裂(set partitioning in hierarchical tree,SPIHT)编码、算术编码相结合的数据压缩方法。为了有效降低数据的冗余度,该方法将采集的...为满足电能质量监测网存储与传输海量录波数据的需要,提出了提升格式的2维离散小波变换、多级树集合分裂(set partitioning in hierarchical tree,SPIHT)编码、算术编码相结合的数据压缩方法。为了有效降低数据的冗余度,该方法将采集的1维电能质量数据按整数倍周期排列为2维矩阵;采用提升格式的2维离散小波变换对数据进行压缩,然后对小波系数进行SPIHT编码,实现了对压缩性能的控制;最后采用算术编码进一步提高了压缩比。对几类常见的电能质量扰动数据进行了压缩实验,证明该方法具有较好的压缩性能。在不同压缩码率下对ATP-EMTP仿真模型得到的扰动数据进行了压缩实验,验证了该方法能通过控制压缩码率实现对压缩性能的控制。展开更多
We introduce in this paper an extension of the Multimodal Compression technique (MC) for the purpose of coding hyperspectral image sequences. The main idea requires few steps, namely: (1) reducing the size of the sequ...We introduce in this paper an extension of the Multimodal Compression technique (MC) for the purpose of coding hyperspectral image sequences. The main idea requires few steps, namely: (1) reducing the size of the sequence by inserting smooth images containing less information into the remaining images of the same sequence, (2) then coding the new compacted sequence using 3D-SPIHT algorithm. In this new scheme, called MC-3D-SPIHT, the insertion is achieved only in the contour of each image, according to a non-supervised way, so that one can preserve the Region of Interest (ROI) quality. For this purpose, a mixing function is employed. After the decoding process, inserted images are extracted by a separation function and the original sequence is reconstructed. By considering data from AVIRIS database, we will show how one decrease significantly the computing time for both coding and decoding.展开更多
文摘为满足电能质量监测网存储与传输海量录波数据的需要,提出了提升格式的2维离散小波变换、多级树集合分裂(set partitioning in hierarchical tree,SPIHT)编码、算术编码相结合的数据压缩方法。为了有效降低数据的冗余度,该方法将采集的1维电能质量数据按整数倍周期排列为2维矩阵;采用提升格式的2维离散小波变换对数据进行压缩,然后对小波系数进行SPIHT编码,实现了对压缩性能的控制;最后采用算术编码进一步提高了压缩比。对几类常见的电能质量扰动数据进行了压缩实验,证明该方法具有较好的压缩性能。在不同压缩码率下对ATP-EMTP仿真模型得到的扰动数据进行了压缩实验,验证了该方法能通过控制压缩码率实现对压缩性能的控制。
文摘We introduce in this paper an extension of the Multimodal Compression technique (MC) for the purpose of coding hyperspectral image sequences. The main idea requires few steps, namely: (1) reducing the size of the sequence by inserting smooth images containing less information into the remaining images of the same sequence, (2) then coding the new compacted sequence using 3D-SPIHT algorithm. In this new scheme, called MC-3D-SPIHT, the insertion is achieved only in the contour of each image, according to a non-supervised way, so that one can preserve the Region of Interest (ROI) quality. For this purpose, a mixing function is employed. After the decoding process, inserted images are extracted by a separation function and the original sequence is reconstructed. By considering data from AVIRIS database, we will show how one decrease significantly the computing time for both coding and decoding.
