Compressed Multi-image Reconstruction Based on Quantization Noise Distribution
Compressed Multi-image Reconstruction Based on Quantization Noise Distribution作者机构:Institute of Image Communication and Information ProcessingShanghai Jiaotong University
出 版 物:《Journal of Donghua University(English Edition)》 (东华大学学报(英文版))
年 卷 期:2007年第24卷第6期
页 面:756-761页
核心收录:
学科分类:0817[工学-化学工程与技术] 08[工学] 0807[工学-动力工程及工程热物理] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程(可授工学、理学学位)] 0802[工学-机械工程] 0811[工学-控制科学与工程]
基 金:The Advanced Research of Shanghai Technical Committee(No.03DZ05020)
主 题:super-resolution quantization noise covariance Bayesian
摘 要:Because of the quantization noise introduced during the compression,super-resolution reconstruction(SRR)techniques are complicated for the compressed *** paper aims to incorporate the prior knowledge of discrete cosine transform(DCT)coefficients into modeling the quantization *** spatial covariance matrix of the quantization noise is estimated by utilizing the Laplacian distribution of the alternating current(AC)*** estimating the spatial joint covariance of overall noises for the imaging system,we propose a general Bayesian framework to enhance the resolution for compressed *** demonstrate the effectiveness of the proposed algorithm and show the superiority to previous methods in objective and subjective aspects.