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We examine the problem of node classification in large-scale and dynamically changing graphs. An entropy-based subgraph extraction method has been developed for extracting subgraphs surrounding the nodes to be classified. We introduce an online version of an existing graph kernel to incrementally compute the kernel matrix for a unbounded stream of these extracted subgraphs. After obtaining the kernel...
Image-domain dual-energy CT (DECT) is practical and critical for medical diagnosis and treatment evaluation. The bottleneck of DECT imaging is the significantly magnified noise after a direct inversion decomposition. A good balance is not readily achievable between noise suppression and spatial resolution maintenance. Noise suppression is conventionally included in DECT decomposition implicitly or...
We present an image-domain point spread function (PSF) modeling approach for resolution recovery where spatially varying PSF kernel widths are adjusted based on data quality. This approach attempts to maximize contrast recovery while minimizing edge artifacts (ringing) associated with PSF modeling. We choose broader PSF kernels for noisier datasets where the extent of ringing is comparable to noise...
Pupil tracking under infrared illumination is an important tool for many researchers in physiological visual optics and ophthalmology. It is also a relevant topic for gaze tracking which is used in psychological and medical research, marketing, human-computer interaction, virtual reality and other areas. A typical setup can be either a low-cost webcam with some infrared LEDs or glasses with mounted...
Motion deblurring is a knotty problem, especially when the photo is shot in a low lighting scene with a long exposure time or a strong reflected lighting scene. In this situation, partially saturated pixels violate the assumption of linear model and the recovered image contains severe ringing artifacts. In this paper, we proposed a novel two-layer images independent deconvolution method that redefine...
With regard to ground-based astronomy observations, due to the interference of atmospheric turbulence, noise and other factors, the observed images are degraded, which makes it difficult to obtain high-resolution astronomical images. In such case, astronomical image restoration is essential. Of all the image deconvolution algorithms, the one based on scaled gradient projection (SGP) is highly effective...
In this paper, we propose a method based on an adaptive active contour modelling to segment the cell nuclei from cervical smear images. The basic idea of our method is to make a contour to adaptively deform so as to get a minimized given region energy function. In order to make the evolution of the contour rely less on the intensity homogeneity and achieve the purpose of adaptive segmentation of the...
Single-image blind deconvolution is a challenging illposed inverse problem which requires regularization techniques to stabilize the restoration process. Its purpose is to recover an underlying blur kernel and a latent image from only one blurred image. In most imaging situations, the blur kernel is not only spatially sparse, but also piecewise smooth with the support of a continuous curve. Thus this...
The inspection, assessment, maintenance and safe operation of the existing civil infrastructure consists one of the major challenges facing engineers today. Such work requires either manual approaches, which are slow and yield subjective results, or automated approaches, which depend upon complex handcrafted features. Yet, for the latter case, it is rarely known in advance which features are important...
Canny Edge Detector is the most widely used operator for edge detection. The problem with Canny is that it outputs a binary edge map, where an edge pixel (edgel) is marked (e.g., its value in the edge map is 255) and a non-edge pixel is unmarked (e.g., its value in the edge map is 0). A typical binary edge map is of low quality, consisting of gaps, notch-like structures, ragged and multi-pixel wide...
SAR image denoising has been an active research topic. Some image denoising methods have been implemented in both spatial and transform domains. Although state-of-the-art denoising methods are numerically impressive, they produce Gibbs-like phenomenon. To solve this problem, we proposed a SAR image denoising algorithm, which is based on dual-domain image denoising (DDID) and cycle-spinning algorithm...
Light is a mixture of multiple spectral components. An image is a response of the scene with respect to these spectra. Principal components are more compact representation of the data compared to any other representations. Hence accuracy of the estimated defocus parameter is higher in principal component representation than any other customary used representations. In this paper, we present comparison...
To print ceaseless tone images, Electrophotographic printers mostly use halftoning method. Scanned pictures procured from such hard transcripts are generally wrecked by screen like antiquities. Recently an approach for reviving relentless image from scanned halftone picture was accomplished. This new model considers both printing deformities and halftone motifs. At first denoising computation is proposed...
Intuitionistic fuzzy edge detection algorithm has been used for the signification or characterization of images. It has been designed by experts and the algorithm provides to aim to minimize errors. However, it has a fixed value for thresholding. In this paper, a hybrid algorithm has been developed using the Otsu method which is calculated a threshold value depending on the images. To be applicable...
Chromatic aberration, caused by photographic lens imperfections, results in the image of only one spectral channel being sharp, while the other channels are blurred depending on their wavelengths difference with the sharp channel. We study chromatic aberration for a system that jointly records color and near-infrared (NIR) images on a single sensor. Chromatic aberration in such a system leads to a...
Application development with hardware description languages (HDLs) such as VHDL or Verilog involves numerous productivity challenges, limiting the potential impact of reconfigurable computing (RC) with FPGAs in high-performance computing. Major challenges with HDL design include steep learning curves, large and complex codes, long compilation times, and lack of development standards across platforms...
This work addresses the problem of automatic wire recognition in images obtained from an unmanned aerial vehicle (UAV). As wires are thin structures it is difficult to extract particular pixels eliminating background. We propose the method that allows detecting wires and estimating their parameters without any human intervention.
Chroma subsampling is commonly used for digital representations of images and video sequences. The basic rationale behind chroma subsampling is that the human visual system is less sensitive to color variations than luma variations. Therefore, chroma data can be coded in lower resolution than luma data, without noticeable loss in perceived image quality. In this paper, we compare different upsampling...
Implementation of a frequency measurement device based on ARM-embedded computer viz. Raspberry Pi is presented. This device is used as a part of a wide area frequency measurement system implemented at Indian Institute of Technology Bombay. Free and open source software is used including Linux based operating system patched with a realtime development framework. This serves as a low-cost high performance...
This paper presents a depth map restoration scheme for both the raw and projected depth map from Kinect v2 sensor. Based on IR-depth consistency, erroneous depth readings around foreground objects are removed by an edge aware consistency correction method. Moreover, a joint adaptive kernel regression algorithm is designed to upsample the sparse depth map after the projection from Kinect v2 sensor's...
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