A novel method of histogram analysis for background extraction in video image is proposed, which is derived from the pixelbased histogram analysis. Not only the statistical property of pixels between temporal frames, ...A novel method of histogram analysis for background extraction in video image is proposed, which is derived from the pixelbased histogram analysis. Not only the statistical property of pixels between temporal frames, but also the corrvlation of local pixels in a single frame is exploited in this method. When carrying out histogram analysis for background extraction, the proposed method is not based on a single pixel but on a 2 × 2 block that has much less computational quantities and can extract a sound background image from video sequence simultaneously. A comparative experiment between the proposed method and the pixel-based histogram analysis shows that the proposed method has a faster speed in background extraction and the obtained background image is better in quantity.展开更多
Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhanc...Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhancement,little of which demonstrates the significant robustness and generalization for diverse real-world underwater scenes.In this paper,we propose an adaptive color correction algorithm based on the maximum likelihood estimation of Gaussian parameters,which effectively removes color casts of a variety of underwater images.A novel algorithm using weighted combination of gradient maps in HSV color space and absolute difference of intensity for accurate background light estimation is proposed,which circumvents the influence of white or bright regions that challenges existing physical model-based methods.To enhance contrast of resultant images,a piece-wise affine transform is applied to the transmission map estimated via background light differential.Finally,with the estimated background light and transmission map,the scene radiance is recovered by addressing an inverse problem of image formation model.Extensive experiments reveal that our results are characterized by natural appearance and genuine color,and our method achieves competitive performance with the state-of-the-art methods in terms of objective evaluation metrics,which further validates the better robustness and higher generalization ability of our enhancement model.展开更多
文摘A novel method of histogram analysis for background extraction in video image is proposed, which is derived from the pixelbased histogram analysis. Not only the statistical property of pixels between temporal frames, but also the corrvlation of local pixels in a single frame is exploited in this method. When carrying out histogram analysis for background extraction, the proposed method is not based on a single pixel but on a 2 × 2 block that has much less computational quantities and can extract a sound background image from video sequence simultaneously. A comparative experiment between the proposed method and the pixel-based histogram analysis shows that the proposed method has a faster speed in background extraction and the obtained background image is better in quantity.
基金supported by Higher Education Scientific Research Project of Ningxia(NGY2017009).
文摘Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhancement,little of which demonstrates the significant robustness and generalization for diverse real-world underwater scenes.In this paper,we propose an adaptive color correction algorithm based on the maximum likelihood estimation of Gaussian parameters,which effectively removes color casts of a variety of underwater images.A novel algorithm using weighted combination of gradient maps in HSV color space and absolute difference of intensity for accurate background light estimation is proposed,which circumvents the influence of white or bright regions that challenges existing physical model-based methods.To enhance contrast of resultant images,a piece-wise affine transform is applied to the transmission map estimated via background light differential.Finally,with the estimated background light and transmission map,the scene radiance is recovered by addressing an inverse problem of image formation model.Extensive experiments reveal that our results are characterized by natural appearance and genuine color,and our method achieves competitive performance with the state-of-the-art methods in terms of objective evaluation metrics,which further validates the better robustness and higher generalization ability of our enhancement model.
