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B. Gidas, "A Renormalization Group Approach to Image Processing Problems," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 2, pp. 164180, February, 1989.  
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@article{ 10.1109/34.16712, author = {B. Gidas}, title = {A Renormalization Group Approach to Image Processing Problems}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {11}, number = {2}, issn = {01628828}, year = {1989}, pages = {164180}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.16712}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  A Renormalization Group Approach to Image Processing Problems IS  2 SN  01628828 SP164 EP180 EPD  164180 A1  B. Gidas, PY  1989 KW  image restoration; computerised picture processing; renormalization group; digital image processing; Markov randomfield modeling; Monte Carlo algorithms; coarsetofine analysis; texture analysis; globaloptimization; multilevel cascode; computerised picture processing; Markov processes; Monte Carlo methods; optimisation VL  11 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
A method for studying problems in digital image processing, based on a combination of renormalization group ideas, the Markov randomfield modeling of images, and metropolistype Monte Carlo algorithms, is presented. The method is efficiently implementable on parallel architectures, and provides a unifying procedure for performing a hierarchical, multiscale, coarsetofine analysis of imageprocessing tasks such as restoration, texture analysis, coding, motion analysis, etc. The method is formulated and applied to the restoration of degraded images. The restoration algorithm is a globaloptimization algorithm applicable to other optimization problems. It generates iteratively a multilevel cascode of restored images corresponding to different levels of resolution, or scale. In the lower levels of the cascade appear the largescale features of the image, and in the higher levels, the microscopic features of the image.
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