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RISS 인기검색어
- 검색키워드
- 저자 : ( Cuiyin Liu ) (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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A Novel Multifocus Image Fusion Algorithm Based on Nonsubsampled Contourlet Transform
( Cuiyin Liu ),( Peng Cheng ),( Shu-qing Chen ),( Cuiwei Wang ),( Fenghong Xiang ) 한국인터넷정보학회 2013 KSII Transactions on Internet and Information Syst Vol.7 No.3
A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate `block effect` and `frequency aliasing` phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.
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A Comprehensive and Practical Image Enhancement Method
( Fanglong Wu ),( Cuiyin Liu ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.10
Image enhancement is a challenging problem in the field of image processing, especially low-light color images enhancement. This paper proposed a robust and comprehensive enhancement method based several points. First, the idea of bright channel is introduced to estimate the illumination map which is used to attain the enhancing result with Retinex model, and the color constancy is keep as well. Second, in order eliminate the illumination offsets wrongly estimated, morphological closing operation is used to modify the initial estimating illumination. Furthermore, in order to avoid fabricating edges, enlarged noises and over-smoothed visual features appearing in enhancing result, a multi-scale closing operation is used. At last, in order to avoiding the haloes and artifacts presented in enhancing result caused by gradient information lost in previous step, guided filtering is introduced to deal with previous result with guided image is initial bright channel. The proposed method can get good illumination map, and attain very effective enhancing results, including dark area is enhanced with more visual features, color natural and constancy, avoiding artifacts and over-enhanced, and eliminating Incorrect light offsets.
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