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This paper proposes a novel model for contrast enhancement of RGB images. The average local contrast measure is increased within a variational framework which preserves the hue of the original image by coupling the channels. The user is enabled to intuitively control the level of the contrast as well as the scale of the enhanced details. Moreover, our model avoids large modifications of the original...
The main purpose of transfer learning is to resolve the problem of different data distribution, generally, when the training samples of source domain are different from the training samples of the target domain. Prediction of salient areas in natural video suffers from the lack of large video benchmarks with human gaze fixations. Different databases only provide dozens up to one or two hundred of...
A large number of images are available on online photo-sharing services along with rich meta-data, including tags, groups, and locations, etc. For associating two domains of different modalities, e.g. images and tags, Canonical Correlation Analysis (CCA) and its extended methods are used widely. We employ a more flexible graph embedding method called Cross-Domain Matching Correlation Analysis (CDMCA),...
An efficient stereo matching algorithm, which applies adaptive smoothness constraints using texture and edge information, is proposed in this work. First, we determine non-textured regions, on which an input image yields flat pixel values. In the non-textured regions, we penalize depth discontinuity and complement the primary CNN-based matching cost with a color-based cost. Second, by combining two...
In this paper, we propose a robust video colorization method automatically through limited color references in a video sequence. The proposed method first estimates motion vectors between a monochrome frame and colored reference frames for initial matching by optical flow. Then it transfers color information to matched points in the monochrome frame and further propagates color information of matched...
Color correction is an essential image processing operation that transforms a camera-dependent RGB color space to a standard color space, e.g., the XYZ or the sRGB color space. The color correction is typically performed by multiplying the camera RGB values by a color correction matrix, which often amplifies image noise. In this paper, we propose an effective color correction pipeline for a noisy...
In this work we introduce a variational nonconvex model for color image regularization. We express the variational problem as an instance of the half quadratic algorithm (HQA). Moreover, the generalized HQA allows us to prove convergence of the variational problem. As a demonstrator of our framework, we consider a vectorial total variation (VTV) formulation with an additional nonconvex pair-wise color-channel...
Color constancy is the ability of the human visual system to perceive constant colors for a surface despite changes in the spectrum of the illumination. In computer vision, the main approach consists in estimating the illuminant color and then to remove its impact on the color of the objects. Many image processing algorithms have been proposed to tackle this problem automatically. However, most of...
We present a per-channel framework for extending monochrome barcodes to color for display applications, offering increased data rates and capacity. Data is independently encoded into barcodes, incorporated within a color image as the red (R), green (G), and blue (B) channels and decoded from the corresponding R, G, and B channels in the image of the displayed barcode captured with a smartphone. Using...
Document is unavailable: This DOI was registered to an article that was not presented by the author(s) at this conference. As per section 8.2.1.B.13 of IEEE's "Publication Services and Products Board Operations Manual," IEEE has chosen to exclude this article from distribution. We regret any inconvenience.
It is well known that many more than three or four spectral measurements are required for accurate measurement of color. Previous work has shown seven to ten measurements can yield accurate results on average, but with significant numbers of errors above the threshold of obvious visual detection. Furthermore, the filters used for these measurements are very difficult to fabricate. We show that such...
Recent advances in image captioning task have led to increasing interests in video captioning task. However, most works on video captioning are focused on generating single input of aggregated features, which hardly deviates from image captioning process and does not fully take advantage of dynamic contents present in videos. We attempt to generate video captions that convey richer contents by temporally...
We propose a salient object detection algorithm via multilevel features learning determined sparse reconstruction. There are three stages in our method. First, the test image are successively processed by a segmentation and semantic information generation procedures. Second, three kinds of features are extracted from semantic, global, and local levels for each superpixel to train a random forest regressor,...
We propose a software solution which allows the user to design a realistic illumination for a given 2D image of a face. The user paints a few strokes on the image to give clues of desired novel lighting effects. The algorithm produces an image of the face under the best possible realistic illumination, accordingly. It takes advantage of a 3D Morphable Model framework and a state of the art inverse...
A novel approach to spatio-temporal saliency detection in video is proposed. Saliency computation is considered as an optimization problem that maximizes the energy of a fully-connected graphical model based on spatio-temporal feature distinctiveness. Each pixel in a video is modeled by a node, and the spatio-temporal feature distinctiveness between pixels by edges connecting the nodes in the graph...
In this paper, we propose a new Multi-kernel Metric Learning (MKML) approach to enhance the performance of person re-identification using adaptive weighted Multi-kernel. The intuition behind our approach is that different features, i.e., low-level and middle-level features, have different nature and thus discriminating capability, utilizing different kernels could map these features into sub-spaces,...
In this paper we introduce a novel decolorization strategy built on image fusion principles. Decolorization (color-to-grayscale), is an important transformation used in many monochrome image processing applications. We demonstrate that aside from color spatial distribution, local information plays an important role in maintaining the discriminability of the image conversion. Our strategy blends the...
In this paper, we propose an algorithm to remove rain streaks from single color image. Firstly, the guided filter, cooperated with rain pixels detection are used to separate a color image into low-frequency and high-frequency parts so that most rain components exist in the high-frequency part. Then, we focus on the high-frequency part to extract the non-rain details according to the characteristics...
If a low dynamic range (LDR) image or video is inverse tone mapped to a higher dynamic range, there can be banding artifacts in the output high dynamic range (HDR) image or video. We design a selective sparse filter to remove the banding artifacts and at the same time preserve edges and details. The filter is able to reduce other artifacts, such as blocky artifacts which are due to the compression...
Intrinsic image decomposition is an important technique that decomposes an image into reflectance and shading components. In this paper, we enable intrinsic decomposition for stereoscopic images. Traditional approaches cannot be directly applied to decompose stereoscopic images, yielding inconsistent reflectance and 3D artifacts after recoloring. To solve this problem, we propose a straight yet effective...
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