Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images
ICIP (2)(2002)
摘要
The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process, The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced, not only to reflect the relative amount of registration error in each low-resolution image, but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.
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关键词
image coding,low-resolution compressed images,adaptive image reconstruction,nonlinear quantization,image resolution,subpixel motion estimation,quantisation (signal),transform coding,motion estimation,high-resolution image reconstruction,image reconstruction,discrete cosine transforms,additive correlated gaussian noise,dct-based compressed images,image sequence,image sequences,frequency aliasing,gaussian noise,image registration,registration error,regularization parameter,quantization,quantization error,moon,low resolution
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