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Automatic estimation and removal of noise on digital image
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作者 Tuananh Nguyen Beomsu Kim Mincheol Hong 《Journal of Measurement Science and Instrumentation》 CAS 2013年第3期256-262,共7页
An spatially adaptive noise detection and removal algorithm is proposed.Under the assumption that an observed image and its additive noise have Gaussian distribution,the noise parameters are estimated with local stati... An spatially adaptive noise detection and removal algorithm is proposed.Under the assumption that an observed image and its additive noise have Gaussian distribution,the noise parameters are estimated with local statistics from an observed degraded image,and the parameters are used to define the constraints on the noise detection process.In addition,an adaptive low-pass filter having a variable filter window defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image.Experimental results demonstrate the capability of the proposed algorithm. 展开更多
关键词 noise estimation DENOISING noise parameters local statistics adaptive filter
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Identifying porphyry-Cu geochemical footprints using local neighborhood statistics in Baft area, Iran
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作者 Saeid GHASEMZADEH Abbas MAGHSOUDI Mahyar YOUSEFI 《Frontiers of Earth Science》 SCIE CAS CSCD 2021年第1期106-120,共15页
Identifying geochemical anomalies related to ore deposition processes facilitates the practice of vectoring toward undiscovered mineral deposit sites.In districtscale exploration studies,analysis of dispersion pattern... Identifying geochemical anomalies related to ore deposition processes facilitates the practice of vectoring toward undiscovered mineral deposit sites.In districtscale exploration studies,analysis of dispersion patterns of ore-forming elements results in more-reliable targets.Therefore,deriving significant geochemical footprints and mapping the ensuing geochemical anomalies are of important issues that lead exploration geologists toward anomaly sources,e.g.,mineralization.This paper aims to examine the effectiveness of local relative enrichment index and singularity mapping technique,as two methods of local neighborhood statistics,in the delineation of anomalous areas for further exploration.A data set of element contents obtained from stream sediment samples in Baft area,Iran,therefore was applied to illustrate the procedure proposed.The close relationship between anomalous patterns recognized and known Cu-occurrences demonstrated that the procedures proposed can efficiently model complex dispersion patterns of geochemical anomalies in the study area.The results showed that singularity mapping method is a better technique,compared to local relative enrichment index,to delineate targets for follow-up exploration in the area.We made this comparison because,as pointed out by exploration geochemists,dispersion patterns of geochemical indicators in stream sediments vary in different areas even for the same deposit type.The variety in the dispersion patterns is due to the operation of post-mineralization subsystems,which are affected by local factors such as landscape of the areas under study.Therefore,the effectiveness of the methods should be evaluated in every area for every targeted deposit. 展开更多
关键词 local neighborhood statistics robust principal component analysis singularity mapping technique local relative enrichment index exploration targets
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