Because of the quantization noise introduced during the compression,super-resolution reconstruction(SRR)techniques are complicated for the compressed images.This paper aims to incorporate the prior knowledge of discre...Because of the quantization noise introduced during the compression,super-resolution reconstruction(SRR)techniques are complicated for the compressed images.This paper aims to incorporate the prior knowledge of discrete cosine transform(DCT)coefficients into modeling the quantization noise.The spatial covariance matrix of the quantization noise is estimated by utilizing the Laplacian distribution of the alternating current(AC)coefficients.After estimating the spatial joint covariance of overall noises for the imaging system,we propose a general Bayesian framework to enhance the resolution for compressed images.Experiments demonstrate the effectiveness of the proposed algorithm and show the superiority to previous methods in objective and subjective aspects.展开更多
A △∑ fractional-N frequency synthesizer fabricated in a 130 nm CMOS technology is presented for the application of an FM tuner. A low noise filter, occupying a small die area and decreasing the output noise, is inte...A △∑ fractional-N frequency synthesizer fabricated in a 130 nm CMOS technology is presented for the application of an FM tuner. A low noise filter, occupying a small die area and decreasing the output noise, is integrated on a chip. A quantization noise suppression technique, using a reduced step size of the frequency divider, is also adopted. The proposed synthesizer needs no off-chip components and occupies an area of 0.7 mm2. The in-band phase noise （from 10 to 100 kHz） below -108 dBc/Hz and out-of-band phase noise of -122.9 dBc/Hz （at 1 MHz offset） are measured with a loop bandwidth of 200 kHz. The quantization noise suppression technique reduces the in-band and out-of band phase noise by 15 dB and 7 dB respectively. The integrated RMS phase error is no more than 0.48°. The proposed synthesizer consumes a total power of 7.4 mW and the frequency resolution is less than 1 Hz.展开更多
基金The Advanced Research of Shanghai Technical Committee(No.03DZ05020)
文摘Because of the quantization noise introduced during the compression,super-resolution reconstruction(SRR)techniques are complicated for the compressed images.This paper aims to incorporate the prior knowledge of discrete cosine transform(DCT)coefficients into modeling the quantization noise.The spatial covariance matrix of the quantization noise is estimated by utilizing the Laplacian distribution of the alternating current(AC)coefficients.After estimating the spatial joint covariance of overall noises for the imaging system,we propose a general Bayesian framework to enhance the resolution for compressed images.Experiments demonstrate the effectiveness of the proposed algorithm and show the superiority to previous methods in objective and subjective aspects.
文摘A △∑ fractional-N frequency synthesizer fabricated in a 130 nm CMOS technology is presented for the application of an FM tuner. A low noise filter, occupying a small die area and decreasing the output noise, is integrated on a chip. A quantization noise suppression technique, using a reduced step size of the frequency divider, is also adopted. The proposed synthesizer needs no off-chip components and occupies an area of 0.7 mm2. The in-band phase noise （from 10 to 100 kHz） below -108 dBc/Hz and out-of-band phase noise of -122.9 dBc/Hz （at 1 MHz offset） are measured with a loop bandwidth of 200 kHz. The quantization noise suppression technique reduces the in-band and out-of band phase noise by 15 dB and 7 dB respectively. The integrated RMS phase error is no more than 0.48°. The proposed synthesizer consumes a total power of 7.4 mW and the frequency resolution is less than 1 Hz.
