라플라시안 피라미드와 주성분 분석을 이용한 가시광과 적외선 영상 합성
Visible and NIR Image Synthesis Using Laplacian Pyramid and Principal Component Analysis
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초록
This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.
Abstract
This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.
참고문헌 (13)
- A. V. Vanmali, "Visible and NIR image fusion using weight-map-guided Laplacian–Gaussian pyramid for improving scene visibility", Sadhana, 42(7), pp.1063~1082 (2017)
- 길태호, "컬러 영상과 근적외선 영상을 이용한 영상 융합", 방송공학회 논문지, 21(4), pp.515~524 (2016), 한국방송∙미디어공학회[DOI]
- Z. Sadeghipoor, "Correlationbased joint acquisition and demosaicing of visible and nearinfrared images", Proc. Int. Conf. on Image Processing, ICIP, pp.3165~3168 (2011)
- X. Zhang, "Enhancing photographs with near infrared images", 26th IEEE Conf. on Comput. Vis. Pattern Recognit., pp.24~26 (2008)
- P. J. Burt, "The Laplacian Pyramid as a Compact Image Code BT", Fundam. Pap. Wavelet Theory, C(4), pp.532~540 (1983)
- R. P. Desale, "Study and analysis of PCA, DCT & DWT based image fusion techniques", Int. Conf. on Signal Process., Image Process. Pattern Recognit, pp.66~69 (2013)
- R. Kaur, "An Approach for Image Fusion using PCA and Genetic Algorithm", Int. J. Comput. Appl, 145(6), pp.54~59 (2016)
- H. J. Kwon, "Radiance map construction based on spatial and intensity correlations between le and SE images for HDR imaging", J. Vis. Commun. Image Represent, 38, pp.695~703 (2016)
- Z. Wang, "No reference perceptual quality assessment of JPEG compressed images", IEEE Int. Conf. Image Process, 1, pp.477~480 (2002)
- M. B. A. Haghighat, "A non-reference image fusion metric based on mutual information of image features", Comput. Electr. Eng, 37(5), pp.744~756 (2011)
- C. T. Vu, "S 3 : A spectral and spatial measure of local perceived sharpness in natural images", IEEE Trans. Image Process, 21(3), pp.934~945 (2012)
- R. Sukthankar, "Smarter presentations : Exploiting homography in camera-projector systems", Proc. IEEE Int. Conf. Comput. Vis, 1, pp.247~253 (2001)
- H. J. Kwon, "CAM-based HDR image reproduction using CA-TC decoupled JCh decomposition", Signal Process. : Image Commun, 70, pp.1~13 (2019)