In Order to reduce the noise in the images and the physical storage, the wavelet-based image compression technique was applied to PIV processing in this paper. To study the effect of the wavelet bases, the standard PI...In Order to reduce the noise in the images and the physical storage, the wavelet-based image compression technique was applied to PIV processing in this paper. To study the effect of the wavelet bases, the standard PIV images were compressed by some known wavelet families, Daubechies, Coifman and Baylkin families with various compression ratios. It was found that a higher order wavelet base provided good compression performance for compressing PIV images. The error analysis of velocity field obtained indicated that the high compression ratio, even up to 64.1, can be realized without losing significant flow information in PIV processing. The wavelet compression technique of PIV was applied to the experimental images of jet flow and showed excellent performance. A reduced number of erroneous vectors can be realized by varying compression ratio. It can say that the wavelet image compression technique is very effective in PIV system.展开更多
To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical mode...To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical model for residual redundancy and a low complexity joint source-channel decoding（JSCD） algorithm are proposed. The complicated residual redundancy in wavelet compressed images is decomposed into several independent 1-D probability check equations composed of Markov chains and it is regarded as a natural channel code with a structure similar to the low density parity check （LDPC） code. A parallel sum-product （SP） and iterative JSCD algorithm is proposed. Simulation results show that the proposed JSCD algorithm can make full use of residual redundancy in different directions to correct errors and improve the peak signal noise ratio （PSNR） of the reconstructed image and reduce the complexity and delay of JSCD. The performance of JSCD is more robust than the traditional separated encoding system with arithmetic coding in the same data rate.展开更多
文摘In Order to reduce the noise in the images and the physical storage, the wavelet-based image compression technique was applied to PIV processing in this paper. To study the effect of the wavelet bases, the standard PIV images were compressed by some known wavelet families, Daubechies, Coifman and Baylkin families with various compression ratios. It was found that a higher order wavelet base provided good compression performance for compressing PIV images. The error analysis of velocity field obtained indicated that the high compression ratio, even up to 64.1, can be realized without losing significant flow information in PIV processing. The wavelet compression technique of PIV was applied to the experimental images of jet flow and showed excellent performance. A reduced number of erroneous vectors can be realized by varying compression ratio. It can say that the wavelet image compression technique is very effective in PIV system.
文摘To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical model for residual redundancy and a low complexity joint source-channel decoding（JSCD） algorithm are proposed. The complicated residual redundancy in wavelet compressed images is decomposed into several independent 1-D probability check equations composed of Markov chains and it is regarded as a natural channel code with a structure similar to the low density parity check （LDPC） code. A parallel sum-product （SP） and iterative JSCD algorithm is proposed. Simulation results show that the proposed JSCD algorithm can make full use of residual redundancy in different directions to correct errors and improve the peak signal noise ratio （PSNR） of the reconstructed image and reduce the complexity and delay of JSCD. The performance of JSCD is more robust than the traditional separated encoding system with arithmetic coding in the same data rate.
