International Journal of Image Processing and Vision Science最新文献

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On the Richardson-Lucy Algorithm with A Varying Point Spread Function along The Iterations 基于变点扩展函数的Richardson-Lucy算法
International Journal of Image Processing and Vision Science Pub Date : 2022-05-01 DOI: 10.47893/ijipvs.2022.1082
Erica S. Souza, Maria Ines Silvani, Gevaldo L. Almeida, Ricardo T. Lopes
{"title":"On the Richardson-Lucy Algorithm with A Varying Point Spread Function along The Iterations","authors":"Erica S. Souza, Maria Ines Silvani, Gevaldo L. Almeida, Ricardo T. Lopes","doi":"10.47893/ijipvs.2022.1082","DOIUrl":"https://doi.org/10.47893/ijipvs.2022.1082","url":null,"abstract":"This work analyses the soundness of two algorithms, Fishsint and Almexp to improve images using the Richardson-Lucy (RL) algorithm under a varying Point Spread Function (PSF) along the iterations. A plethora of methods based on Richardson-Lucy has been published, but no further proposal involving such an alternative has been published. Whereas the unnamed predecessor of Fishsint addressed only small size synthetic images under a blind fashion procedure, Fishsint and Almexp employs an algorithm Wdet to determine the initial PSF and all subsequent values after each iteration, respectively. Fishsint performs a loop, where the last determined PSF improves the previously obtained image and vice versa. Its original unnamed version has been modified in the present work by entering a previously determined initial PSF to accelerate the convergence. The algorithm Almexp, as well, uses the algorithm Wdet to determine the PSF of the last obtained image to deconvolve itself. Therefore, whereas the Fishsint unnamed predecessor used an initial guess PSF - chosen by the customer - Almexp determines the PSF always through the algorithm Wdet.\u0000\u0000Fishsint and Almexp furnish final images which outperform those obtained with the original Richardson-Lucy approach working under a constant PSF along the iterations. Hence, in order to carry out a comparison between their performances, all the algorithms have been embedded into an ad hoc written Fortran 90 program. The results corroborate the soundness of a varying PSF along the iterations with the Richardson Lucy algorithm.\u0000\u0000Keywords: Richardson-Lucy, varying PSF along iterations, image improvement, neutron radiography","PeriodicalId":349750,"journal":{"name":"International Journal of Image Processing and Vision Science","volume":"7 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121955275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Digital Image Processing. 数字图像处理。
International Journal of Image Processing and Vision Science Pub Date : 2022-05-01 DOI: 10.47893/ijipvs.2022.1083
A. Deshpande
{"title":"Digital Image Processing.","authors":"A. Deshpande","doi":"10.47893/ijipvs.2022.1083","DOIUrl":"https://doi.org/10.47893/ijipvs.2022.1083","url":null,"abstract":"Digital image processing is the use of a digital computer to process a digital image using an algorithm. As a subcategory or area of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as noise accumulation and distortion during processing. This review article provides a comprehensive literature review of various image processing techniques along with a brief introduction to digital image processing that defines its scope and importance, thereby highlighting the importance of its use in the field of electronic engineering applications that are used in today's commercial and industrial scenarios. It takes into consideration the research work done by various leading scholars in the field of electronic engineering and also the description of various software tools like MATLAB which is used for the practical implementation of the given problem lying in its domain.","PeriodicalId":349750,"journal":{"name":"International Journal of Image Processing and Vision Science","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Nonlinear Spectral Unmixing using Semi-Supervised Standard Fuzzy Clustering 基于半监督标准模糊聚类的非线性光谱解混
International Journal of Image Processing and Vision Science Pub Date : 2022-05-01 DOI: 10.47893/ijipvs.2022.1084
Shaheera Rashwan
{"title":"Nonlinear Spectral Unmixing using Semi-Supervised Standard Fuzzy Clustering","authors":"Shaheera Rashwan","doi":"10.47893/ijipvs.2022.1084","DOIUrl":"https://doi.org/10.47893/ijipvs.2022.1084","url":null,"abstract":"Coarse resolution captured in remote sensing causes the combination of different materials in one pixel, called the mixed pixel. Spectral unmixing estimates the combination of endmembers in mixed pixels and their corresponding abundance maps in the Hyper/Multi spectral image. In this paper, a nonlinear spectral unmixing based on semi-supervised fuzzy clustering is proposed. First, pure pixels (endmembers) using Vertex Component Analysis (VCA) are extracted and those pixels are the labelled pixels where the membership value of each is 1 for the corresponding endmember and 0 for the others. Second, the semi-supervised fuzzy clustering is applied to find the membership matrix defining the fraction of the endmember in each mixed pixel and hence extract the abundance maps. The experiments were conducted on both synthetic data such as the Legendre data and real data such as Jasper Ridge data. The non-linearity of the Legendre data was performed by the Fan model on different signal-tonoise ratio values. The results of the new unmixing model show its significant performance when compared with four state-of the art unmixing algorithms","PeriodicalId":349750,"journal":{"name":"International Journal of Image Processing and Vision Science","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127731425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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