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Saliency Detection in Textured Images
2020 15th International Conference on Computer Science & Education (ICCSE), 2020Recently, salient object detection has achieved significant development. Unfortunately, existing methods mainly depend on color differences, not effective for textured images. This is because the visual patterns of textures cannot be well measured with existing methods.
Yu Zeng, Biyu Wan
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Change detection, Remote sensing image, Saliency map, Visual saliency model.
Computer Graphics, Imaging and Visualisation (CGIV 2007), 2007A new approach of using HNN with multi-connect architecture in color image recognition has been produced in this work. HNN consists of a single layer of fully connected processing elements, which is described as an associative memory. However, HNN is useless in dealing with data not in bipolar representation.
Kussay Nugamesh Mutter +2 more
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Saliency-Guided Image Style Transfer
2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2019In this paper, we propose an automatic saliency-guide style transfer method, which deploys style transfer to the salient object in an image. Our method can generate a new artwork form of image, which aggregates the characteristics of real-world images and artistic images.
Xiuwen Liu +3 more
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Image co-saliency detection via locally adaptive saliency map fusion
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017Co-saliency detection aims at discovering the common and salient objects in multiple images. It explores not only intra-image but extra inter-image visual cues, and hence compensates the shortages in single-image saliency detection. The performance of co-saliency detection substantially relies on the explored visual cues.
Chung-Chi Tsai +2 more
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Saliency Modeling from Image Histograms
2012We proposed a computational visual saliency modeling technique. The proposed technique makes use of a color co-occurrence histogram (CCH) that captures not only "how many" but also "where and how" image pixels are composed into a visually perceivable image.
Shijian Lu, Joo-Hwee Lim
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Saliency based natural image understanding
The First Asian Conference on Pattern Recognition, 2011This paper presents a novel method for natural image understanding. We improved the effect of saliency detection for the purpose of image segmentation at first. Then Graph cuts are used to find global optimal segmentation of N-dimensional image. After that, we adopt the scheme of supervised learning to classify the scene type of the image.
null Qingshan Li +2 more
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Image deblurring using saliency detection
2014 Recent Advances in Engineering and Computational Sciences (RAECS), 2014Motion deblurring is a vastly used technique in image processing and is an interesting task in this field. In this paper an algorithm is proposed for the detection of saliency to create boundaries of the object under observation. In the next step segmentation of the image is performed to separate the image from the background.
null Johar A., null Kalra GS.
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Saliency-Guided Deep Neural Networks for SAR Image Change Detection
IEEE Transactions on Geoscience and Remote Sensing, 2019Change detection is an important task to identify land-cover changes between the acquisitions at different times. For synthetic aperture radar (SAR) images, inherent speckle noise of the images can lead to false changed points, which affects the change ...
Jie Geng +3 more
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SAR Image Change Detection Using PCANet Guided by Saliency Detection
IEEE Geoscience and Remote Sensing Letters, 2019The selection of training samples is important for the accuracy and efficiency of the synthetic aperture radar (SAR) image change detection task. However, training samples are traditionally extracted from the whole image, which leads to longer training ...
Mengke Li +5 more
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Brushstroke Control from Image Saliency
2011 IEEE Ninth International Symposium on Parallel and Distributed Processing with Applications Workshops, 2011Increasing the level of detail (LOD) in brushstrokes within areas of interest improved the realism of painterly rendering. Using a modified quad-tree, we segmented an image into areas with similar levels of saliency, each of these segments was then used to control the brush strokes during rendering.
Hochang Lee +3 more
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