Deep Learning Algorithms for Single Image Deraining

被引：0

作者：

Grigoras, Radu ^{[1
]}

Ciocoiu, Iulian B. ^{[1
]}

机构：

[1] Gheorghe Asachi Tech Univ Iasi, Iasi, Romania

来源：

PROCEEDINGS OF THE 2018 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI) | 2018年

关键词：

deraining; deep learning; redundant representation; Gaussian Mixture Models; SPARSE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Three deep learning based algorithms are compared in terms of standard figures of merit and visual quality for single image deraining. The comparative analysis additionally considers several classic approaches based on redundant representations or Gaussian Mixture Models. Experimental results are reported for both synthetic and real images, revealing higher quality of the neural based approaches.

引用

页数：4

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