The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. F...The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.展开更多
In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detect...In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detection. This paper presents a fuzzy adaptive image contrast enhancement algorithm based on gray entropy. This method not only enhances the overall image contrast, but also effectively enrich the target image detail information, and suppress the noise amplification. Meanwhile, the paper proposes an improved K and P parameters image restoration algorithm. The algorithm combines both isotropic and anisotropic diffusion, the use of regional differences in the frequency achieved in the different regions use different iterative equation. Experimental results show that the algorithm with TV model algorithm compared with the same premise of restorative effects, avoiding the staircase effect and better than the TV model repair speed.展开更多
An improved single image dehazing method based on dark channel prior and wavelet transform is proposed. This proposed method employs wavelet transform and guided filter instead of the soft matting procedure to estimat...An improved single image dehazing method based on dark channel prior and wavelet transform is proposed. This proposed method employs wavelet transform and guided filter instead of the soft matting procedure to estimate and refine the depth map of haze images. Moreover, a contrast enhancement method based on just noticeable difference(JND) and quadratic function is adopted to enhance the contrast for the dehazed image, since the scene radiance is usually not as bright as the atmospheric light,and the dehazed image looks dim. The experimental results show that the proposed approach can effectively enhance the haze image and is well suitable for implementing on the surveillance and obstacle detection systems.展开更多
基金National Natural Science Foundation of China(No.61271357)International S&T Cooperation Program of Shanxi Province(No.2013081035)
文摘The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.
文摘In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detection. This paper presents a fuzzy adaptive image contrast enhancement algorithm based on gray entropy. This method not only enhances the overall image contrast, but also effectively enrich the target image detail information, and suppress the noise amplification. Meanwhile, the paper proposes an improved K and P parameters image restoration algorithm. The algorithm combines both isotropic and anisotropic diffusion, the use of regional differences in the frequency achieved in the different regions use different iterative equation. Experimental results show that the algorithm with TV model algorithm compared with the same premise of restorative effects, avoiding the staircase effect and better than the TV model repair speed.
基金supported by the National Natural Science Foundation of China(61075013)the Joint Funds of the Civil Aviation(61139003)
文摘An improved single image dehazing method based on dark channel prior and wavelet transform is proposed. This proposed method employs wavelet transform and guided filter instead of the soft matting procedure to estimate and refine the depth map of haze images. Moreover, a contrast enhancement method based on just noticeable difference(JND) and quadratic function is adopted to enhance the contrast for the dehazed image, since the scene radiance is usually not as bright as the atmospheric light,and the dehazed image looks dim. The experimental results show that the proposed approach can effectively enhance the haze image and is well suitable for implementing on the surveillance and obstacle detection systems.
