Homomorphic enhancement of infrared images using the additive wavelet transform

被引:31
作者
Ashiba, H.I. [1 ]
Awadallah, K.H. [1 ]
El-Halfawy, S.M. [1 ]
Abd El-Samie, F.E. [1 ]
机构
[1] Faculty of Electronic Engineering, Menouf
关键词
Additives - Image enhancement - Infrared imaging - Reflection - Image compression;
D O I
10.2528/PIERC08012301
中图分类号
学科分类号
摘要
This paper presents a new enhancement technique for infrared images. This technique combines the benefits of homomorphic image processing and the additive wavelet transform. The idea behind this technique is based on decomposing the image into subbands in an additive fashion using the additive wavelet transform. This transform gives the image as an addition of subbands of the same resolution. The homomorphic processing is performed on each subband, separately. It is known that the homomorphic processing on images is performed in the log domain which transforms the image into illumination and reflectance components. Enhancement of the reflectance reinforces details in the image. So, applying this process in each subband enhances the details of the image in each subband. Finally, an inverse additive wavelet transform is performed on the homomorphic enhanced subbands to get an infrared image with better visual details. © 2018, Electromagnetics Academy. All rights reserved.
引用
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页码:123 / 130
页数:7
相关论文
共 9 条
[1]  
Qi H., Head J.F., Asymmetry Analysis Using Automatic Segmentation and Classification for Breast Cancer Detection in Thermograms, (2002)
[2]  
Kuruganti P.T., Qi H., Asymmetry analysis in breast cancer detection using thermal infrared images, Proceedings of the Second Joint EMBS/BMES Conference, USA, (2002)
[3]  
Scales N., Herry C., Frize M., Automated image segmentation for breast analysis using infrared images, Proceedings of the 26Th Annual International Conference of the IEEE EMBS, (2004)
[4]  
Zhang C.J., Yang F., Wang X.D., Zhang H.R., An efficient non-linear algorithmfor contrast enhancement of infrared image, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, (2005)
[5]  
Qil H., Snyder W.E., Head J.F., Elliott R.L., Detecting breast cancer from infrared images by asymmetry analysis, Proceedings of the 22Nd Annual EMBS International Conference, (2000)
[6]  
Andreone L., Antonello P.C., Bertozzi M., Broggi A., Fascioli A., Ranzato D., Vehicle detection and localization in infra-red images, The IEEE 5Th International Conference on Intelligent Transportation Systems, (2002)
[7]  
Zhang C., Wang X., Zhang H., Lv G., Wei H., A reducing multi-noise contrast enhancement algorithm for infrared image, Proceedings of the First International Conference on Innovative Computing, Information and Control (ICICIC’06), (2006)
[8]  
Nunez J., Otazu X., Fors O., Prades A., Pala V., Arbiol R., Multiresolution-based image fusion with additive wavelet decomposition, IEEE Trans. Geosci. Remote Sensing, 37, 3, pp. 1204-1211, (1999)
[9]  
Lim J.S., Two-Dimensional Signal and Image Processing, (1990)