Today, digital cameras are widely used in taking photos. However, some photos lack detail and need enhancement. Many existing image enhancement algorithms are patch based and the patch size is always fixed throughout ...Today, digital cameras are widely used in taking photos. However, some photos lack detail and need enhancement. Many existing image enhancement algorithms are patch based and the patch size is always fixed throughout the image. Users must tune the patch size to obtain the appropriate enhancement. In this study,we propose an automatic image enhancement method based on adaptive patch selection using both dark and bright channels. The double channels enhance images with various exposure problems. The patch size used for channel extraction is selected automatically by thresholding a contrast feature, which is learned systematically from a set of natural images crawled from the web. Our proposed method can automatically enhance foggy or under-exposed/backlit images without any user interaction. Experimental results demonstrate that our method can provide a significant improvement in existing patch-based image enhancement algorithms.展开更多
An adaptive contrast enhancement (ACE) algorithm is presented in this paper, in which the contrast gain is determined by mapping the local standard deviation (LSD) histogram of an image to a Gaussian distribution func...An adaptive contrast enhancement (ACE) algorithm is presented in this paper, in which the contrast gain is determined by mapping the local standard deviation (LSD) histogram of an image to a Gaussian distribution function. The contrast gain is nonlinearly adjusted to avoid noise overenhancement and ringing artifacts while improving the detail contrast with less computational burden. The effectiveness of our method is demonstrated with radiological images and compared with other algorithms.展开更多
基金Project supported by the Zhejiang Provincial Natural Science Foundation of China(Nos.LY17F020009 and LQ14F020003)the National Natural Science Foundation of China(No.61303143)the Professional Development Project for Domestic Visiting Scholars in Universities of Zhejiang Provincial Education Department(Research on Image Stylization Based on Samples)
文摘Today, digital cameras are widely used in taking photos. However, some photos lack detail and need enhancement. Many existing image enhancement algorithms are patch based and the patch size is always fixed throughout the image. Users must tune the patch size to obtain the appropriate enhancement. In this study,we propose an automatic image enhancement method based on adaptive patch selection using both dark and bright channels. The double channels enhance images with various exposure problems. The patch size used for channel extraction is selected automatically by thresholding a contrast feature, which is learned systematically from a set of natural images crawled from the web. Our proposed method can automatically enhance foggy or under-exposed/backlit images without any user interaction. Experimental results demonstrate that our method can provide a significant improvement in existing patch-based image enhancement algorithms.
基金the National Natural Science Foundation of China(No:3 963 0 1 1 0 ) the National Key Technologies R&D Programme under Con-tract96-92 0 -1 2 -0 1
文摘An adaptive contrast enhancement (ACE) algorithm is presented in this paper, in which the contrast gain is determined by mapping the local standard deviation (LSD) histogram of an image to a Gaussian distribution function. The contrast gain is nonlinearly adjusted to avoid noise overenhancement and ringing artifacts while improving the detail contrast with less computational burden. The effectiveness of our method is demonstrated with radiological images and compared with other algorithms.
