In order to satisfy the need of diagnoses,based on the characteristic of medical images that a sequence of frames are formed in one body inspection,a new strategy for medical images compression is proposed.The 3-D wav...In order to satisfy the need of diagnoses,based on the characteristic of medical images that a sequence of frames are formed in one body inspection,a new strategy for medical images compression is proposed.The 3-D wavelet is adopted and the planar zerotree is extended to the 3-D zerotree.By making use of the 3-D zerotree structure,a simple method for region of interest(ROI)mask generation is put forward.Medical images are compressed by three-dimensional embedded coding with the compression of regions of interest.Simulation results have shown that it can efficiently improve the compression ratio without affecting the diagnoses.展开更多
The paper describes an efficient lossy and lossless three dimensional (3D) image compression of hyperspectral images. The method adopts the 3D spatial-spectral hybrid transform and the proposed transform-based coder. ...The paper describes an efficient lossy and lossless three dimensional (3D) image compression of hyperspectral images. The method adopts the 3D spatial-spectral hybrid transform and the proposed transform-based coder. The hybrid transforms are that Karhunen-Loève Transform (KLT) which decorrelates spectral data of a hyperspectral image, and the integer Discrete Wavelet Transform (DWT) which is applied to the spatial data and produces decorrelated wavelet coefficients. Our simpler transform-based coder is inspired by Shapiro’s EZW algorithm, but encodes residual values and only implements dominant pass incorporating six symbols. The proposed method will be examined on AVIRIS images and evaluated using compression ratio for both lossless and lossy compression, and signal to noise ratio (SNR) for lossy compression. Experimental results show that the proposed image compression not only is more efficient but also has better compression ratio.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.60272050).
文摘In order to satisfy the need of diagnoses,based on the characteristic of medical images that a sequence of frames are formed in one body inspection,a new strategy for medical images compression is proposed.The 3-D wavelet is adopted and the planar zerotree is extended to the 3-D zerotree.By making use of the 3-D zerotree structure,a simple method for region of interest(ROI)mask generation is put forward.Medical images are compressed by three-dimensional embedded coding with the compression of regions of interest.Simulation results have shown that it can efficiently improve the compression ratio without affecting the diagnoses.
文摘The paper describes an efficient lossy and lossless three dimensional (3D) image compression of hyperspectral images. The method adopts the 3D spatial-spectral hybrid transform and the proposed transform-based coder. The hybrid transforms are that Karhunen-Loève Transform (KLT) which decorrelates spectral data of a hyperspectral image, and the integer Discrete Wavelet Transform (DWT) which is applied to the spatial data and produces decorrelated wavelet coefficients. Our simpler transform-based coder is inspired by Shapiro’s EZW algorithm, but encodes residual values and only implements dominant pass incorporating six symbols. The proposed method will be examined on AVIRIS images and evaluated using compression ratio for both lossless and lossy compression, and signal to noise ratio (SNR) for lossy compression. Experimental results show that the proposed image compression not only is more efficient but also has better compression ratio.
