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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...
In this paper, we introduce a multi-dimensional approach to the problem of reconstruction of MR image sequences that are highly undersampled in k-space. By formulating the reconstruction as a high-order low-rank plus sparse tensor decomposition problem, we propose an efficient numerical algorithm based on the alternating direction method of multipliers (ADMM) to solve the optimization. Through extensive...
Visual question answering (VQA) comes as a result of great development in computer vision and natural language processing, which requires deep understanding of images and questions and effective integration of them. Current works on VQA simply concatenated visual and textual features or compared them via dot product, which were unable to eliminate the semantic difference between them. We argue to...
Hazy images hinder image understanding in many applications such as autonomous vehicle. In this paper, we propose an efficient method to improve image quality of hazy images. Our method estimates the transmission function based on a linear model that allows efficient computation and employs quadtree to search for a region that best represents the scatter of airlight. Experiments were conducted using...
We present an application of the Layer-wise Relevance Propagation (LRP) algorithm to state of the art deep convolutional neural networks and Fisher Vector classifiers to compare the image perception and prediction strategies of both classifiers with the use of visualized heatmaps. Layer-wise Relevance Propagation (LRP) is a method to compute scores for individual components of an input image, denoting...
This paper presents a new convex optimization method for the image dehazing problem. It is based on reformulation of the hazed image model to solve the bilinearly coupled hazed image and light transmission distribution term as a single optimization variable. This resolves the nonconvex difficulty of the original problem and is sufficient for straightforward reconstruction of the haze free image. The...
Real-time operation and low-power dissipation in video coding systems have become important research challenges, especially in mobile devices with limited battery and computational resources. There are many video coding standards coexisting in the market nowadays, so it is important for current devices to support different video coding standards. This paper presents a multi-standard luminance sub-samples...
Lossless image coding process predicts the value of current pixel from previously decoded pixel values. Then the prediction error is classified according to the context model. This classification splits the sources with different distributions and hence reduce the total entropy of the prediction error signals. In the literature, the predictor has been intensively studied. Some evolutionary approaches...
Our challenge is the design of a “universal” bit-efficient image compression approach. The prime goal is to allow reconstruction of images with high quality. In addition, we attempt to design the coder and decoder “universal”, such that MPEG-7-like low-and mid-level descriptors are an integral part of the coded representation. To this end, we introduce a sparse Mixture-of-Experts regression approach...
This paper considers the Softcast joint source-channel video coding scheme for data transmission over parallel channels with different power constraints and noise characteristics, typical in DSL or PLT channels. To minimize the mean square error at receiver, an optimal precoding matrix design problem has to be solved, which requires the solution of an inverse eigenvalue problem. Such solution is taken...
The accuracy of end-to-end distortion (EED) estimation is crucial to achieving effective error resilient video coding. An established solution, the recursive optimal per-pixel estimate (ROPE), does so by tracking the first and second moments of decoder-reconstructed pixels. An alternative estimation approach, the spectral coefficient-wise optimal recursive estimate (SCORE), tracks instead moments...
In this paper we propose a new quality metric to estimate the impact of packet loss on the perceptual quality of encoded video sequences transmitted over error-prone networks. The proposed metric, henceforth referred to as Cumulative Distortion using Structural Similarity (CDSSIM), quantifies the overall structural distortion resulting from bidirectional error propagation in predictively coded, motion...
A joint source-channel rate-distortion (RD) optimization is proposed for video communication systems. The source coding and channel coding options are optimized by seeking the best trade-off between the estimated end-to-end distortion of a video packet and the sum of the number of source bits and forward error correction bits used to encode that packet. The proposed RD algorithm controls the total...
Subjective experimental results are widely used as the ground truth in objective Image Quality Assessment (IQA). Specifically, Pairwise Comparison method has superiority over Mean Opinion Scores (MOS), but there is a problem when measuring the consistency between subjective pairwise comparisons and objective quality predictions. In this paper, we first analyze the existing problem of current evaluation...
Conventional autofocus methods based on contrast detection are often unable to reliably decide the direction of initial lens movement. In this paper, we show that even using the disparity data obtained from blurry stereo images can effectively solve the problem. This approach is developed for stereo cameras with adjustable focal distance. Such stereo cameras provide sharp images over a wide range...
In this paper, we propose a novel reduced-reference quality assessment metric for image super-resolution (RRIQA-SR) based on the low-resolution (LR) image information. First, we use the Markov Random Field (MRF) to model the pixel correspondence between LR and high-resolution (HR) images. Based on the pixel correspondence, we predict the perceptual similarity between image patches of LR and HR images...
Due to its importance, figure/ground segmentation in video has gained interest recently. The key factor of the segmentation is the construction of the spatio-temporal coherence. Previous works usually use the motion approximation as a measurement of the coherence, resulting in a low accuracy. In this paper, we present a novel method to measure the coherence, and an algorithm for target segmentation...
In this paper, a tetrahedral mesh-based approach is investigated for 3D image segmentation on a given image volume. We present a series of algorithms to generate high quality, feature-sensitive, and adaptive meshes to partition a 3D volume, where the 3D Canny edge detector is utilized to preserve important feature boundaries in the generated tetrahedral mesh. Each cluster of voxels within a tetrahedron...
High efficiency video coding (HEVC) standard is within the block-based hybrid coding framework, which essentially adopts prediction unit (PU) as the basic motion compensation unit. However, in the case of tiny motion, the actual motion vectors (MVs) for each sample may differ from the PU's MV, thus resulting in more residual energy. In this paper, a novel pixel-wise motion refinement method (PMR)...
The demands for high quality multimedia contents and the advent of the Ultra High Definition (UHD) resolution have motivated the development of the High Efficiency Video Coding (HEVC) standard, which outperforms prior standards by up to 50% in terms of coding efficiency. This improvement, however, involves higher computational complexity in the encoder side, making it essential for realtime encoders...
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