This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color information.First,conventional subband synthesis b...This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color information.First,conventional subband synthesis based color reproduction techniques do not consider the noise during image acquisition and assume that the CFA data are noiseless.To tackle the noisy CFA data,a novel approach is proposed by inserting a subband denoising scheme into the conventional subband synthesis framework.Second,conventional subband synthesis based techniques exploit the decimated wavelet transform that is not shift-invariant and could result in ringing artifacts in the result.To alleviate these artifacts,the directional cycle-spinning（DCS） technique is exploited.Furthermore,a new cycle-spinning pattern is proposed according to the sampling pattern of the Bayer CFA data.Extensive experiments are conducted to demonstrate that the proposed approach outperforms several approaches.展开更多
In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at ...In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at lowest level, while correlated noise gets removed by only a fraction at lower levels, so we used multilevel thresholding on curvelet coefficients. The threshold in the proposed method depends on the variance of curvelet coefficients, the mean and the median of absolute curvelet coefficients at a particular level which makes it adaptive in nature. Results obtained for 2-D images demonstrate an improved performance over other recent related methods available in literature.展开更多
基金supported by the National Natural Science Foundation of China(6087212360972133)+2 种基金the Joint Fund of the National Natural Science Foundation and the Guangdong Provincial Natural Science Foundation(U0835001)the Fundamental Research Funds for the Central Universities,SCUT(x2dxD2105260) the Fund of Provincial Key Laboratory for Computer Information Processing Technology(KJS0922)
文摘This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color information.First,conventional subband synthesis based color reproduction techniques do not consider the noise during image acquisition and assume that the CFA data are noiseless.To tackle the noisy CFA data,a novel approach is proposed by inserting a subband denoising scheme into the conventional subband synthesis framework.Second,conventional subband synthesis based techniques exploit the decimated wavelet transform that is not shift-invariant and could result in ringing artifacts in the result.To alleviate these artifacts,the directional cycle-spinning（DCS） technique is exploited.Furthermore,a new cycle-spinning pattern is proposed according to the sampling pattern of the Bayer CFA data.Extensive experiments are conducted to demonstrate that the proposed approach outperforms several approaches.
基金supported in part by the University Grants Commission,New Delhi,India under Grant No. F.No.36-246/2008(SR)
文摘In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at lowest level, while correlated noise gets removed by only a fraction at lower levels, so we used multilevel thresholding on curvelet coefficients. The threshold in the proposed method depends on the variance of curvelet coefficients, the mean and the median of absolute curvelet coefficients at a particular level which makes it adaptive in nature. Results obtained for 2-D images demonstrate an improved performance over other recent related methods available in literature.
