Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of wat...Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.展开更多
In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on t...In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on the vehicle detection. Thus, features from a foggy road image are surveyed through experinmlts, and a histogram is caloalated with the bright value. The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly. If the high density area, from the view point of histogram, is applied with the stretching method, the definition of the image can be increased. On this fact, this paper proposed a method to divide the histogram and to determine applicable range of the stretching method. The improved results by the proposed methods are proved with the camparison tests between the proposed and previous methods.展开更多
This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of...This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.展开更多
trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalize...trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.展开更多
Aiming at the problem in infrared image enhancement,a new method is given based on histogram.Using the gray characteristics of target,the upper-bound threshold is selected adaptively and the histogram is processed by ...Aiming at the problem in infrared image enhancement,a new method is given based on histogram.Using the gray characteristics of target,the upper-bound threshold is selected adaptively and the histogram is processed by the threshold.After choosing the gray transform function based on the gray level distribution of image,the gray transformation is done during histogram equalization.Finally,the enhanced image is obtained.Compared with histogram equalization(HE),histogram double equalization(HDE) and plateau histogram equalization(PE),the simulation results demonstrate that the image enhancement effect of this method has obvious superiority.At the same time,its operation speed is fast and real-time ability is excellent.展开更多
An efficient novel algorithm was developed to estimate the Density of States(DOS) for large systems by calculating the ensemble means of an extensive physical variable, such as the potential energy, U, in generalized ...An efficient novel algorithm was developed to estimate the Density of States(DOS) for large systems by calculating the ensemble means of an extensive physical variable, such as the potential energy, U, in generalized canonical ensembles to interpolate the interior reverse temperature curve β_s(U)=SU/U, where S(U) is the logarithm of the DOS. This curve is computed with different accuracies in different energy regions to capture the dependence of the reverse temperature on U without setting prior grid in the U space. By combining with a U-compression transformation, we decrease the computational complexity from O(N3/2) in the normal Wang Landau type method to O(N1/2) in the current algorithm, as the degrees of freedom of system N. The efficiency of the algorithm is demonstrated by applying to Lennard Jones fluids with various N, along with its ability to find different macroscopic states, including metastable states.展开更多
基金supported by the National Natural Science Foundation of China (No. 61401413)
文摘Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.
基金supported by the MKE(The Ministry of Knowledge Economy),Koreathe ITRC(Information Technology Research Center)support program(NIPA-2010-(C1090-1021-0010))the Brain Korea 21 Project in 2010
文摘In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on the vehicle detection. Thus, features from a foggy road image are surveyed through experinmlts, and a histogram is caloalated with the bright value. The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly. If the high density area, from the view point of histogram, is applied with the stretching method, the definition of the image can be increased. On this fact, this paper proposed a method to divide the histogram and to determine applicable range of the stretching method. The improved results by the proposed methods are proved with the camparison tests between the proposed and previous methods.
基金supported by the Brain Korea 21 Project in 2011 and MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.
基金Supported by the Natural Science Foundation of China(No.61311140262,61171163,61271021)
文摘trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.
文摘Aiming at the problem in infrared image enhancement,a new method is given based on histogram.Using the gray characteristics of target,the upper-bound threshold is selected adaptively and the histogram is processed by the threshold.After choosing the gray transform function based on the gray level distribution of image,the gray transformation is done during histogram equalization.Finally,the enhanced image is obtained.Compared with histogram equalization(HE),histogram double equalization(HDE) and plateau histogram equalization(PE),the simulation results demonstrate that the image enhancement effect of this method has obvious superiority.At the same time,its operation speed is fast and real-time ability is excellent.
基金supported by the National Natural Science Foundation of China(Grant No.11175250)the Open Project Grant from the StateKey Laboratory of Theoretical PhysicsZhou X thanks the financial support of the Hundred of Talents Program in Chinese Academy of Sciences
文摘An efficient novel algorithm was developed to estimate the Density of States(DOS) for large systems by calculating the ensemble means of an extensive physical variable, such as the potential energy, U, in generalized canonical ensembles to interpolate the interior reverse temperature curve β_s(U)=SU/U, where S(U) is the logarithm of the DOS. This curve is computed with different accuracies in different energy regions to capture the dependence of the reverse temperature on U without setting prior grid in the U space. By combining with a U-compression transformation, we decrease the computational complexity from O(N3/2) in the normal Wang Landau type method to O(N1/2) in the current algorithm, as the degrees of freedom of system N. The efficiency of the algorithm is demonstrated by applying to Lennard Jones fluids with various N, along with its ability to find different macroscopic states, including metastable states.
