IEEE Transactions on Image Processing

Due to several sources of multipath in through-wall radar sensing, such as walls, floors, and ceilings, there could exist multipath ghosts associated with a few genuine targets in the synthetic aperture beamformed image. The multipath ghosts are false ...

Switching the liquid crystal display (LCD) backlight of a portable multimedia device to a low power level saves energy but results in poor image quality especially for the low-luminance image areas. In this paper, we propose an image enhancement ...

The sparsity of images in a transform domain or dictionary has been exploited in many applications in image processing. For example, analytical sparsifying transforms, such as wavelets and discrete cosine transform (DCT), have been extensively used in ...

Block transform coded images usually suffer from annoying artifacts at low bit rates, caused by the coarse quantization of transform coefficients. In this paper, we propose a new method to reduce compression artifacts by the overlapped-block transform ...

Video based human body pose estimation seeks to estimate the human body pose from an image or a video sequence, which captures a person exhibiting some activities. To handle noise and occlusion, a pose prior model is often constructed and is ...

Two novel unsupervised dimensionality reduction techniques, termed sparse distance preserving embedding (SDPE) and sparse proximity preserving embedding (SPPE), are proposed for feature extraction and classification. SDPE and SPPE perform in the clean ...

Image recovery from undersampled data has always been challenging due to its implicit ill-posed nature but becomes fascinating with the emerging compressed sensing (CS) theory. This paper proposes a novel gradient based dictionary learning method for ...

Most tracking-by-detection algorithms train discriminative classifiers to separate target objects from their surrounding background. In this setting, noisy samples are likely to be included when they are not properly sampled, thereby causing visual ...

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform ...

Exploiting the sparsity within representation models for images is critical for image denoising. The best currently available denoising methods take advantage of the sparsity from image self-similarity, pre-learned, and fixed representations. Most of ...

Recently, the median filtering (MF) detector as a forensic tool for the recovery of images' processing history has attracted wide interest. This paper presents a novel method for the blind detection of MF in digital images. Following some strongly ...

This paper presents a new automatic image annotation algorithm. First, we introduce a new similarity measure between images: compactness. This uses low level visual descriptors for determining the similarity between two images. Compactness shows how ...

Compressed sensing (CS) is an important theory for sub-Nyquist sampling and recovery of compressible data. Recently, it has been extended to cope with the case where corruption to the CS data is modeled as impulsive noise. The new formulation, termed as ...

This paper introduces a novel method of image reconstruction from a finite number of projections by processing the image along parallel rays. The geometry from the image plane is transferred to the Cartesian lattice by means of using the original image'...

In pedestrian detection, as sophisticated feature descriptors are used for improving detection accuracy, its processing speed becomes a critical issue. In this paper, we propose a novel speed-up scheme based on multiple-instance pruning (MIP), one of ...

This paper initially develops the discrete-point sampling operator's concept, model, and parameters that we have previously proposed, and makes its belt-shaped regions in a discrete-point sampling map more salient and appropriate for centerline ...

A novel component-level dictionary learning framework that exploits image/video group characteristics based on sparse representation is introduced in this paper. Unlike the previous methods that select the dictionaries to best reconstruct the data, we ...

Multilevel thresholding amounts to segmenting a gray-level image into several distinct regions. This paper presents a 2D histogram based multilevel thresholding approach to improve the separation between objects. Recent studies indicate that the results ...

In this paper, we present a syntactic string matching approach to solve the frontal face recognition problem. String matching is a powerful partial matching technique, but is not suitable for frontal face recognition due to its requirement of globally ...

In this paper, we propose a novel feature adaptive co-segmentation method that can learn adaptive features of different image groups for accurate common objects segmentation. We also propose image complexity awareness for adaptive feature learning. In ...

A new method for video watermarking is presented in this paper. In the proposed method, data are embedded in the LL subband of wavelet coefficients, and decoding is performed based on the comparison among the elements of the first principal component ...

We present a new upsampling method to enhance the spatial resolution of depth images. Given a low-resolution depth image from an active depth sensor and a potentially high-resolution color image from a passive RGB camera, we formulate it as an adaptive ...

Multidimensional linear phase perfect reconstruction filter bank (MDLPPRFB) can be designed and implemented via lattice structure. The lattice structure for the MDLPPRFB with filter support ${\cal N}({\rm M}\Xi)$ has been published by Muramatsu et. al. ,...

This paper proposes a new super-resolution (SR) scheme for landmark images by retrieving correlated web images. Using correlated web images significantly improves the exemplar-based SR. Given a low-resolution (LR) image, we extract local descriptors ...

Estimating the amount of blur in a given image is important for computer vision applications. More specifically, the spatially varying defocus point-spread-functions (PSFs) over an image reveal geometric information of the scene, and their estimate can ...

A model of visual masking, which reveals the visibility of stimuli in the human visual system (HVS), is useful in perceptual based image/video processing. The existing visual masking function mainly considers luminance contrast, which always ...

Multiresolution strategies are commonly used in the nonrigid registration to avoid local minima in the optimization space. Generally, a step-by-step hierarchical approach is adopted, in which the registration starts on a level with reduced complexity (...

The sensitivity of the human visual system decreases dramatically with increasing distance from the fixation location in a video frame. Accurate prediction of a viewer's gaze location has the potential to improve bit allocation, rate control, error ...

Reconstruction of unknown objects by microwave illumination requires efficient inversion for measured electromagnetic scattering data. In the integral equation approach for reconstructing dielectric objects based on the Born iterative method or its ...

This paper addresses the problem of combining multiple radar images of the same scene to produce a more informative composite image. The proposed approach for probabilistic fuzzy logic-based image fusion automatically forms fuzzy membership functions ...