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Dilated Convolutional Transformer for High-Quality image Deraining

Dilated Convolutional Transformer for High-Quality Image Der...

引用

ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： Yufeng Li Jiyang Lu Hongming Chen Xianhao Wu Xiang Chen College of Electronic and Information Engineering Shenyang Aerospace University School of Computer Science and Engineering Nanjing University of Science and Technology

Convolutional neural networks (CNNs) and Transformers have achieved significant success in image signal processing. However, little effort has been made to effectively combine the properties of these two architectures to satisfy image deraining. In this paper, we propose an effective de-raining method, dilated convolutional Transformer (DCT), which can enlarge the receptive fields of the network to aggregate global information. The fundamental building unit of our approach is the dilformer block containing multi-dilconv sparse attention (MDSA) and multi-dilconv feed-forward network (MDFN). The MDSA calculates the multi-scale query to generate accurate similarity map so that rich multi-scale information can be better utilized for the high-quality image reconstruction. In addition, we adopt ReLU to replace the original softmax to enforce sparsity in the Transformer for better feature aggregation. The MDFN is further established to better integrate the rain information of different scales in the feature transformation. Extensive experiments on the benchmarks show the favorable performance against state-of-the-art approaches.

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Empirical performance analysis of linear discriminant classifiers

Empirical performance analysis of linear discriminant classi...

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conference on computer Vision and pattern recognition (CVPR)

作者： W. Zhao R. Chellappa N. Nandhakumar Center for Automation Research University of Maryland College Park MD USA Image & Video Processing LG ERCA Inc. NJ USA

In face recognition literature, holistic template matching systems and geometrical local feature based systems have been pursued. In the holistic approach, PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) are popular ones. More recently, the combination of PCA and LDA has been proposed as a superior alternative over pure PCA and LDA. In this paper, we illustrate the rationales behind these methods and the pros and cons of applying them to pattern classification task. A theoretical performance analysis of LDA suggests applying LDA over the principal components from the original signal space or the subspace. The improved performance of this combined approach is demonstrated through experiments conducted on both simulated data and real data.

关键词： Performance analysis Linear discriminant analysis Principal component analysis Face recognition pattern recognition Bayesian methods Degradation Density functional theory Automation Educational institutions

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A Markov random field model-based approach to image interpretation

A Markov random field model-based approach to image interpre...

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conference on computer Vision and pattern recognition (CVPR)

作者： J.W. Modestino J. Zhang Dept. of Electr. Comput. & Syst. Eng. Rensselaer Polytech. Inst. Troy New York NY USA Department of Electrical Engineering and Computer Science University of Wisconsin Milwaukee Milwaukee WI USA Electrical Computer and System Engineering Department Rensselaer Polytechnic Institute RPI Troy NY USA

A Markov random field (MRF) model-based approach to automated image interpretation is described and demonstrated as a region-based scheme. In this approach, an image is first segmented into a collection of disjoint regions which form the nodes of an adjacency graph. image interpretation is then achieved through assigning object labels, or interpretations, to the segmented regions, or nodes, using domain knowledge, extracted feature measurements, and spatial relationships between the various regions. The interpretation labels are modeled as a MRF on the corresponding adjacency graph, and the image interpretation problem are formulated as a maximum a posteriori estimation rule. Simulated annealing is used to find the best realization, or optimal interpretation. Through the MRF model, this approach also provides a systematic method for organizing and representing domain knowledge through the clique functions of the probability density function underlying MRF. Results of image interpretation experiments performed on synthetic and real-world images using this approach are described.< >

关键词： Markov random fields image segmentation image edge detection Integrated circuit modeling Feature extraction image processing Layout Systems engineering and theory Erbium Biomedical measurements

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An affine invariant tensor dissimilarity measure and its applications to tensor-valued image segmentation

An affine invariant tensor dissimilarity measure and its app...

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conference on computer Vision and pattern recognition (CVPR)

作者： Zhizhou Wang B.C. Vemuri Department of CISE University of Florida Gainesville FL USA

Tensor fields specifically, matrix valued data sets, have recently attracted increased attention in the fields of image processing. computer vision, visualization and medical imaging. In this paper, we present a novel definition of tensor "distance" grounded in concepts from information theory and incorporate it in the segmentation of tensor-valued images. In some applications, a symmetric positive definite (SPD) tensor at each point of a tensor valued image can be interpreted as the covariance matrix of a local Gaussian distribution. Thus, a natural measure of dissimilarity between SPD tensors would be the KL divergence or its relative. We propose the square root of the J-divergence (symmetrized KL) between two Gaussian distributions corresponding to the tensors being compared that leads to a novel closed form expression. Unlike the traditional Frobenius norm-based tensor distance, our "distance" is affine invariant, a desirable property in many applications. We then incorporate this new tensor "distance" in a region based active contour model for bimodal tensor field segmentation and show its application to the segmentation of diffusion tensor magnetic resonance images (DT-MRI) as well as for the texture segmentation problem in computer vision. Synthetic and real data experiments are shown to depict the performance of the proposed model.

关键词： Tensile stress image segmentation Application software computer vision Gaussian distribution Magnetic field measurement image processing Data visualization Biomedical imaging Information theory

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Scale space localization, blur, and contour-based image coding

Scale space localization, blur, and contour-based image codi...

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conference on computer Vision and pattern recognition (CVPR)

作者： J.H. Elder S.W. Zucker Computer Science Division NEC Research Institute Inc. Princeton NJ USA Centre for Intelligent Machines McGill University Montreal QUE Canada

We have recently proposed a scale-adaptive algorithm for reliable edge detection and blur estimation. The algorithm produces a contour code which consists of estimates of position, brightness, contrast and blur for each edge point in the image. Here we address two questions: 1. Can scale adaptation be used to achieve precise localization of blurred edges? 2. How much of the perceptual content of an image is carried by the 1-D contour code? We report an efficient algorithm for subpixel localization, and show that local scale control allows excellent precision even for highly blurred edges. We further show how local scale control can quantitatively account for human visual acuity of blurred edge stimuli. To address the question of perceptual content, we report an algorithm for inverting the contour code to reconstruct an estimate of the original image. While reconstruction based on edge brightness and contrast alone introduces significant artifact, restitution of the local blur signal is shown to produce perceptually accurate reconstructions.

关键词： image coding image edge detection image reconstruction Filters Detectors computer science National electric code Brightness Humans Stereo image processing

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A Time-Efficient Cascade for Real-Time Object Detection: With applications for the visually impaired

A Time-Efficient Cascade for Real-Time Object Detection: Wit...

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ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： Xiangrong Chen A.L. Yuille Department of Statistics University of California Los Angeles CA USA

Real-time object detection is essential for many computer vision applications. Many rapid detection algorithms are based on using cascades of tests. But existing design criteria for cascades either ignore the time complexity of the tests or make over-simplified assumptions about them. This paper gives a criterion for designing a time-efficient cascade that explicitly takes into account the time complexity of tests (as evaluated by computer run time) including the time for pre-processing. We design a greedy algorithm to minimize this criterion (noting that the full problem is NP-complete). Finally, we illustrate our method on the task of text detection in city scenes. This gives a text detection algorithm that runs at 0.025 seconds per 320×240 image, which is equivalent to 40 frames per second. This is a speed up factor of 2.5 compared to our previous text detector. It gives a realtime system which can be used for applications to help the blind and visually impaired.

关键词： Object detection Testing Application software Detection algorithms computer vision Algorithm design and analysis Greedy algorithms Cities and towns Layout Detectors

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Ordinal measures for visual correspondence

Ordinal measures for visual correspondence

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conference on computer Vision and pattern recognition (CVPR)

作者： D.N. Bhat S.K. Nayar Department of Computes Science Columbia University NY USA

We present ordinal measures for establishing image correspondence. Linear correspondence measures like correlation and the sum of squared differences are known to be fragile. Ordinal measures, which are based on relative ordering of intensity values in windows, have demonstrable robustness to depth discontinuities, occlusion and noise. The relative ordering of intensity values in each window is represented by a rank permutation which is obtained by sorting the corresponding intensity data. By using a novel distance metric between the rank permutations, we arrive at ordinal correlation coefficients. These coefficients are independent of absolute intensity scale, i.e. they are normalized measures. Further, since rank permutations are invariant to monotone transformations of the intensity values, the coefficients are unaffected by nonlinear effects like gamma variation between images. We have developed a simple algorithm for their efficient implementation. Experiments suggest the superiority of ordinal measures over existing techniques under non-ideal conditions. Though we present ordinal measures in the context of stereo, they serve as a general tool for image matching that is applicable to other vision problems such as motion estimation and image registration.

关键词： Layout Motion estimation Signal to noise ratio Reflection Cameras Noise measurement Noise robustness Motion measurement Reflectivity Stereo image processing

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A layered approach to stereo reconstruction

A layered approach to stereo reconstruction

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conference on computer Vision and pattern recognition (CVPR)

作者： S. Baker R. Szeliski P. Anandan Department of Computer Science Columbia University New York NY USA Microsoft Research Microsoft Corporation Redmond WA USA

We propose a framework for extracting structure from stereo which represents the scene as a collection of approximately planar layers. Each layer consists of an explicit 3D plane equation, a colored image with per-pixel opacity (a sprite), and a per-pixel depth offset relative to the plane. Initial estimates of the layers are recovered using techniques taken from parametric motion estimation. These initial estimates are then refined using a re-synthesis algorithm which takes into account both occlusions and mixed pixels. Reasoning about such effects allows the recovery of depth and color information with high accuracy even in partially occluded regions. Another important benefit of our framework is that the output consists of a collection of approximately planar regions, a representation which is far more appropriate than a dense depth map for many applications such as rendering and video parsing.

关键词： Layout image reconstruction Pixel Motion estimation Cameras Stereo image processing computer science Read only memory Equations Sprites (computer)

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Deformable models with parameter functions: application to heart-wall modeling

Deformable models with parameter functions: application to h...

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ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： Park Metaxas Young Department of Computer & Information Science University of Pennsylvania Philadelphia PA USA Department of Radiology University of Pennsylvania Philadelphia PA USA

This paper develops a new class of physics-based deformable models which can deform both globally and locally. Their global parameters are functions allowing the definition of new parameterized primitives and parameterized global deformations. These new global parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional bending and twisting. Using a physics-based approach we convert these geometric models into deformable models that deform due to forces exerted from the data-points so as to conform to the given dataset. We present an experiment involving the extraction of shape and motion of the Left Ventricle (LV) of a heart from MRI-SPAMM data based on a few global parameter functions.< >

关键词： Biomedical imaging, MRI Machine vision image processing Biomedical imaging Cardiography

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Radiometric self calibration

Radiometric self calibration

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conference on computer Vision and pattern recognition (CVPR)

作者： T. Mitsunaga S.K. Nayar Media Processing Laboratories Sony Corporation Japan Department of Computer Science Columbia University USA

A simple algorithm is described that computes the radiometric response function of an imaging system, from images of an arbitrary scene taken using different exposures. The exposure is varied by changing either the aperture setting or the shutter speed. The algorithm does not require precise estimates of the exposures used. Rough estimates of the ratios of the exposures (e.g. F-number settings on an inexpensive lens) are sufficient for accurate recovery of the response function as well as the actual exposure ratios. The computed response function is used to fuse the multiple images into a single high dynamic range radiance image. Robustness is tested using a variety of scenes and cameras as well as noisy synthetic images generated using 100 randomly selected response curves. Automatic rejection of image areas that have large vignetting effects or temporal scene variations make the algorithm applicable to not just photographic but also video cameras.

关键词： Radiometry Calibration Layout Cameras Apertures Lenses Fuses Dynamic range Robustness Testing

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