Contrast limited adaptive histogram equalization
Graphics gems IV
Image enhancement by unsharp masking the depth buffer
ACM SIGGRAPH 2006 Papers
ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
A multiscale image enhancement method for calcification detection in screening mammograms
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Novel Image Enhancement Algorithm Based on Wavelet Multiscale
ICINIS '10 Proceedings of the 2010 Third International Conference on Intelligent Networks and Intelligent Systems
A wireless vehicle surveillance system mixed QoS controls
International Journal of Wireless and Mobile Computing
Gray-scale image enhancement as an automatic process driven by evolution
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Human Visual System-Based Image Enhancement and Logarithmic Contrast Measure
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image information and visual quality
IEEE Transactions on Image Processing
Sharpness Enhancement of Stereo Images Using Binocular Just-Noticeable Difference
IEEE Transactions on Image Processing
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
Automatic semantic annotation by using fuzzy theory for natural images
International Journal of Wireless and Mobile Computing
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The outdoor stereo vision systems which can be used to observe objects from multiple directions are affected by fog and haze thus causing a serious decline in visibility. Therefore, using image enhancement approaches in fog and haze stereoscopic systems can alleviate blurred images, help grasp the situation of road traffic from a three-dimensional point of view and improve visibility. In order to solve the limitations of stereoscopic simulation and traffic safety caused by the weather, we propose a novel contrast enhancement method of fog and haze stereoscopic images based on mobile computing to improve image quality in this paper. The proposed approach decomposes the original image of left and right views into wavelet domain, highlights the low-frequency coefficients by edge sharpening, and enhances it by modifications of high-frequency coefficients. Experimental results show that the proposed approach outperforms conventional approaches, provides more pleasant viewing and alleviates fog and haze phenomena.