Compressed Multi-image Reconstruction Based on Quantization Noise Distribution

作     者：程燕 方向忠 

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.