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Two simple methods are described for fusing the outputs of hyperspectral rare target detection algorithms to achieve more consistent results across a variety of images and objects of interest. The methods are demonstrated with atmospherically corrected (spectral reflectance) visible/near-infrared/shortwave-infrared and long-wavelength infrared hyperspectral imagery using five different detection algorithms...
Motion estimation is an important component for video processing and compression. A fast spatiotemporal statistical information based motion estimation technique is proposed in this paper. It uses the spatiotemporal correlation in the image sequence to detect and to estimate global motion, based which a block matching approach is applied for more accurate motion estimation. The experimental results...
A task of no-reference visual quality metric verification is considered. A test set that contains 500 JPEG format images having different distortions is created. The results of experiments carried out by 316 volunteer observers to evaluate visual quality of images are presented. The experiments allowed obtaining mean opinion scores (MOS) based on averaging the evaluations. Several non-reference image...
Image quality assessment is becoming increasingly used in many applications. In most of the existing image quality assessment approaches, the main objective is to develop measures that are consistent with the subjective evaluation. Therefore, the performance of a given image quality metric is evaluated against the MOS determined from a series of subjective tests performed on a database. A plethora...
Contrast is one of the most relevant perceptual and quality factors in digital images and measuring it is not a trivial task. We have carried out an online psychophysical experiment to register perceived contrast. The results from the observers indicate that color images are rated higher than their respective greyscale one indicating that contrast is influenced color. A two-sided sign test at 5% level...
The Grassberger-Procaccia (GP) algorithm is investigated in estimating ID of hyperspectral imagery. Due to the high data dimensionality and large pairwise pixel distance, data dimensionality may need to be pre-reduced such that the trade-off can be achieved between taking the scale r small enough to have an accurate estimate and taking the r sufficiently large to reduce statistical errors due to lack...
The piece-wise convex multiple model endmember detection algorithm (P-COMMEND) and the Piece-wise Convex End-member detection (PCE) algorithm autonomously estimate many sets of endmembers to represent a hyperspectral image. A piece-wise convex model with several sets of endmembers is more effective for representing non-convex hyperspectral imagery over the standard convex geometry model (or linear...
Hyperspectral image data with sub-centimeter spatial resolution acquired by a low-altitude imaging system provided us valuable insight for the biochemistry. However, it is rather difficult to utilize the spatially detailed information because of the spectral fluctuation caused by the structural factor, e.g. BRDF, specular components, shading. This paper provides a statistical method for the estimation...
A novel texture classification method of matching co- occurrence matrices (CMs) on statistical manifold is presented. The manifold framework is stemmed from the assumption that the co-occurred pixel pairs of a texture image under a specific parameter setting is a realization of underlying probability distribution. The dissimilarity between texture images can be evaluated by the divergence between...
Random Walks has less interaction, better accuracy and higher computing independency. We introduce local intensity entropy to modify the weight function in Random Walks, in order to consider not only the intensity change of adjacent pixels, but also the statistical features of regions. Then we put forward a real-time interactive object extraction system for high resolution remote sensing images based...
It's the key for regional landslide susceptivity assessment to confirm the regional landslide susceptivity factors. Cameron Highlands of Malaysia was selected as the study area. Bivariate statistical analysis method and ArcGIS were used for analyzing the relationships among landslides and environmental factors. Then, Probability Index Model was developed with Landslide Area Density. Lastly, the assessment...
This paper proposes a novel improved median filter algorithm for the images highly corrupted with salt-and-pepper noise. Firstly all the pixels are classified into signal pixels and noisy pixels by using the Max-Min noise detector. The noisy pixels are then separated into three classes, which are low-density, moderate-density, and high-density noises, based on the local statistic information. Finally...
The orientation code is a quantization of pixel gradient orientation. It has the most important characteristic of illumination invariant and has become an important template matching method. In order to improve accuracy and real time ability of the original algorithm, we present a new conception of relative orientation code (ROC), and design template matching method based on the ROC. This method first...
This paper describes a novel, yet effective model for automatically evaluating or quantifying the visual quality of a distorted image against its reference, based on the image statistical information. Image statistical information is embedded into the proposed model via a set of singular values, extracted using SVD, each of which characterizes the dynamics of image energy. Alterations of singular...
A new image retrieval method, which is based on an optimum matched cluster-pairs set between two images and referred to as IROMCS, is proposed. it uses assignment model to seek an optimum matched cluster-pairs set. Based on an optimum matched cluster-pairs set, a similarity measure is defined. Since the matching algorithm study the similarity of two clusters based on these two scales both color and...
Lane detection and tracking is still a challenging task. Here, we combine the recently introduced Statistical Hough transform (SHT) with a Particle Filter (PF) and show its application for robust lane tracking. SHT improves the standard Hough transform (HT) which was shown to work well for lane detection. We use the local descriptors of the SHT as measurement for the PF, and show how a new three kernel...
Top-down class-specific knowledge is crucial for accurate image segmentation, as low-level color and texture cues alone are insufficient to identify true object boundaries. However, existing methods such as conditional random field models (CRFs) generally impose the class-specific knowledge only at the “node” level, evaluating class membership probabilities at the (super)pixels that define the random...
We present a real-time multi-sensor architecture for video-based pedestrian detection used within a road side unit for intersection assistance. The entire system is implemented on available PC hardware, combining a frame grabber board with embedded FPGA and a graphics card into a powerful processing network. Giving classification performance top priority, we use HOG descriptors with a Gaussian kernel...
Image registration is an indispensable process in the detection of brain structural and anatomical abnormities. Inverse-consistency, topology preserving and real time application are essential to provide accurate deformation fields for statistical analysis of brain variability. Unfortunately, the previous algorithms lacked of these features. We present a registration method by adapting the optimization...
Given very few images containing a common object of interest under severe variations in appearance, we detect the common object and provide a compact visual representation of that object, depicted by a binary sketch. Our algorithm is composed of two stages: (i) Detect a mutually common (yet non-trivial) ensemble of `self-similarity descriptors' shared by all the input images. (ii) Having found such...
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