Topic
Channel (digital image)
About: Channel (digital image) is a research topic. Over the lifetime, 7211 publications have been published within this topic receiving 69974 citations.
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01 Aug 2018
TL;DR: Wang et al. as discussed by the authors proposed a novel convolutional neural network based on wavelet and dark channel to extract dark channel of rain image as a feature map in network and achieved haze removal in an indirect way.
Abstract: Rain removal from a single image is a challenge which has been studied for a long time. In this paper, a novel convolutional neural network based on wavelet and dark channel is proposed. On one hand, we think that rain streaks correspond to high frequency component of the image. Therefore, haar wavelet transform is a good choice to separate the rain streaks and background to some extent. More specifically, the LL subband of a rain image is more inclined to express the background information, while HL, LH subband tend to represent the rain streaks and the edges respectively. On the other hand, the accumulation of rain streaks from long distance makes the rain image look like haze veil. We extract dark channel of rain image as a feature map in network. By increasing this mapping between the dark channel of input and output images, we achieve haze removal in an indirect way. All of the parameters are optimized by back-propagation. Experiments on both synthetic and realworld datasets reveal that our method outperforms other state-of-the-art methods from a qualitative and quantitative perspective.
23 citations
TL;DR: This work revisits the framework for brain-coupled image search, where the Electroencephalography (EEG) channel under rapid serial visual presentation protocol is used to detect user preferences and proposes a different perspective on iterative coupling.
Abstract: We revisit the framework for brain-coupled image search, where the Electroencephalography (EEG) channel under rapid serial visual presentation protocol is used to detect user preferences. Extending previous works on the synergy between content-based image labeling and EEG-based brain-computer interface (BCI), we propose a different perspective on iterative coupling. Previously, the iterations were used to improve the set of EEG-based image labels before propagating them to the unseen images for the final retrieval. In our approach we accumulate the evidence of the true labels for each image in the database through iterations. This is done by propagating the EEG-based labels of the presented images at each iteration to the rest of images in the database. Our results demonstrate a continuous improvement of the labeling performance across iterations despite the moderate EEG-based labeling (AUC <75%). The overall analysis is done in terms of the single-trial EEG decoding performance and the image database reorganization quality. Furthermore, we discuss the EEG-based labeling performance with respect to a search task given the same image database.
23 citations
TL;DR: The private key of DFrRT is the high-frequency component related to the plaintext in this paper, which means the proposed cryptosystem is able to resist various types of attacks and maintain the asymmetric characteristics of the cryptos system.
23 citations
TL;DR: It is shown that the fringe-adjusted filtering can be effectively applied to a multichannel single-output JTC to obtain excellent correlation discrimination between an unknown input scene target and a reference image for all color channels.
Abstract: A fringe-adjusted joint transform correlator (JTC) based technique for improved color pattern recognition is introduced. in the proposed technique, a real-valued fringe-adjusted filter is used to reshape the joint power spectrum to yield better correlation output. A color image is processed through three channels, and fringe-adjusted filtering is applied to each of these channels to achieve excellent correlation discrimination. The correlation outputs from these channels are then fused together to make a decision on the detection of a desired color pattern. It is also shown that the fringe-adjusted filtering can be effectively applied to a multichannel single-output JTC to obtain excellent correlation discrimination between an unknown input scene target and a reference image for all color channels. The proposed techniques can be implemented in real time for practical color pattern recognition applications. Two architectures for all-optical implementation of the proposed techniques are presented.
23 citations
Patent•
23 Aug 1993
TL;DR: In this paper, a method for generating a 3D spatial image that has a greatly improved three-dimensional (3D) effect was proposed. But this method requires a series of two dimensional stereoscopic image pairs which have been composed by different scenes photographed on different bases or computer generated using a single channel or multi-channel optical image projector, beam splitter, camera, and a retro-reflective screen.
Abstract: A method for generating a three-dimensional spatial image that has a greatly improved three-dimensional (3-D) effect. The method utilizes a series of two dimensional stereoscopic image pairs which have been composed by different scenes photographed on different bases or computer generated using a single channel or multi-channel optical image projector, beam splitter, camera, and a retro-reflective screen.
23 citations