Deep Neural Networks for HDR imaging
نویسنده
چکیده
We propose novel methods of solving two tasks using Convolutional Neural Networks, firstly the task of generating HDR map of a static scene using differently exposed LDR images of the scene captured using conventional cameras and secondly the task of finding an optimal tone mapping operator that would give a better score on the TMQI metric compared to the existing methods. We quantitatively show the performance of our networks and illustrate the cases where our networks performs good as well as bad.
منابع مشابه
Provide a Deep Convolutional Neural Network Optimized with Morphological Filters to Map Trees in Urban Environments Using Aerial Imagery
Today, we cannot ignore the role of trees in the quality of human life, so that the earth is inconceivable for humans without the presence of trees. In addition to their natural role, urban trees are also very important in terms of visual beauty. Aerial imagery using unmanned platforms with very high spatial resolution is available today. Convolutional neural networks based deep learning method...
متن کاملExpandNet
High dynamic range (HDR) imaging provides the capability of handling real world lighting as opposed to the traditional low dynamic range (LDR) which struggles to accurately represent images with higher dynamic range. However, most imaging content is still available only in LDR. This paper presents a method for generating HDR content from LDR content based on deep Convolutional Neural Networks (...
متن کاملLearning-based Image Enhancement for Visual Odometry in Challenging HDR Environments
One of the main open challenges in visual odometry (VO) is the robustness to difficult illumination conditions or high dynamic range (HDR) environments. The main difficulties in these situations come from both the limitations of the sensors and the inability to perform a successful tracking of interest points because of the bold assumptions in VO, such as brightness constancy. We address this p...
متن کاملDeep Chain HDRI: Reconstructing a High Dynamic Range Image from a Single Low Dynamic Range Image
In this paper, we propose a novel deep neural network model that reconstructs a high dynamic range (HDR) image from a single low dynamic range (LDR) image. The proposed model is based on a convolutional neural network composed of dilated convolutional layers, and infers LDR images with various exposures and illumination from a single LDR image of the same scene. Then, the final HDR image can be...
متن کاملNeural Imaging Using Single-Photon Avalanche Diodes
Introduction: This paper analyses the ability of single-photon avalanche diodes (SPADs) for neural imaging. The current trend in the production of SPADs moves toward the minimumdark count rate (DCR) and maximum photon detection probability (PDP). Moreover, the jitter response which is the main measurement characteristic for the timing uncertainty is progressing. Methods: The neural imaging pro...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1611.00591 شماره
صفحات -
تاریخ انتشار 2016