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Low-noise CMOS image sensors (CIS) employing column-parallel amplifiers that significantly reduce temporal noise, as well as electron-multiplication CCD (EM-CCD) image sensors are becoming popular for very-low-light-level imaging. This paper presents a column-parallel ADC for CMOS imagers using a successive operation of folding-integration ADC (FI-ADC) and cyclic ADC for attaining very low noise,...
Using a set of low resolution images with sub-pixel shifts to reconstruct a high resolution less aliased image requires both interleaving of the image samples at the effectively higher sampling rate and deconvolution of the blur introduced by pixel sensor averaging. When measurement noise is low and knowledge of sub-pixel shift values is accurate, resolution improvement is limited primarily by the...
Segmentation in echo-cardiographic images is a difficult task due to the presence of speckle noise, low contrast and blurring. We present a novel method based on clustering performed in the feature space. A new feature-based image representation is proposed. It is obtained by computing a local feature descriptor at every pixel location. This descriptor is derived using the Radon-Transform to effectively...
In this paper a new synthetic test sequence for evaluation of mosquito noise (MN) due to video codecs is presented with accompanying detection algorithm. The approach and methodology are based on a specially designed test pattern that highlights the MN artefacts. Because of its codec independence, MN can be measured for all types of compression methods like MPEG-1, MPEG-2, H.264, XVid, DivX.. A micro...
In this paper, we propose a content-aware noise reduction (NR) method for the Digital TV, which preserves image textures and edges. In the proposed method, noise is first reduced by a temporal recursive NR filter and then further suppressed by a spatial NR filter. To preserve the image texture, the saliency map which accurately represents edges in a noisy image is employed in the spatial filter. Experimental...
To solve the contradiction between the noise-reducing effect and the time complexity of the standard median filter algorithm, the paper proposed an improved median filter algorithm combined with average filtering. According to the correlation of the image, the algorithm adaptively resizes the filter mask according to noise levels of the mask. According to the sorting results of the selected pixel...
The interest points detection of foreground (moving) objects in videostreams is one of the key step in such applications as: path tracking, computer vision etc. The points of interest should have several features as: few interest points in each moving object, they should be well localized. This conditions are fulfilled by corners of moving objects. The requirements which desirable for a corner detectors...
This paper proposes a novel two-stage denoising method for removing random-valued impulse noise from an image. First, an impulse noise detection scheme is used to detect the pixels which are likely to be corrupted by the impulse noise (called the noise candidates). Then the noise candidates are reconstructed by using the image inpainting method based on sparse representation in an iterative manner...
The using of binary affine transformation for simultaneous encryption-decryption of two images the same dimension that are clearly marked internal contours.
The measure of detecting the surface edge information of cold-roll steel sheets has been investigated rely on the digital image processing toolbox of the mathematic software MATLAB, and the edge detecting experiment of surface grayscale image has been conducted on the computer. The method of detecting defects such as black flecks and scratching has been realized in the research, the different effect...
Energy infrastructure is a critical underpinning of modern society. To ensure its safe and healthy operation, a wide-area situational awareness system is essential to provide high-resolution understanding of the system dynamics such that proper actions can be taken in time in response to power system disturbances and to avoid cascading blackouts. This paper focusses on the high resolution or finer-scale...
The use of digital images of scanned handwritten historical documents has increased in recent years, especially with the online availability of large document collections. However, the sheer number of images in some of these collections makes them cumbersome to manually read and process, making the need for automated processing of increased importance. A key step in the recognition and retrieval of...
In this paper we present an adaptive sharpening algorithm for restoration of an image which has been corrupted by mild blur, and strong noise. Most existing adaptive sharpening algorithms can not handle strong noise well due to the intrinsic contradiction between sharpening and de-noising. To solve this problem we propose an algorithm that is capable of capturing local image structure and sharpness,...
Stereo vision is the process of recovering 3D spatial information from a pair of 2D images. It is very difficult problem due to the fact that stereo matching problem tends to produce as large number of plausible solutions. Thus we need to restrict the solution space in some manner. Trellis-based stereo matching algorithm places hard constraints on the solution by considering the geometry of stereo...
In this paper, a novel approach is proposed for unsupervised change detection of multitemporal remote sensing images. The proposed method is able to produce the change detection result on the difference image without a priori assumptions .Firstly, the difference image which is acquired from multitemporal images. Mean shift algorithm is used to reduce noise of difference image and fake change. Then...
The mixels in the hyperspectral images directly influence the accuracy of target recognition. The ICE algorithm doesn't extract the endmembers based on the hypothesis of the pure pixels' existence, and gets good performance in the spectral unmixing application. After analyzing the theory of the the ICE algorithm and nonnegative matrix factorization, the method of hyperspectral image unmixing via endmembers'...
The Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) is a parametric mixture-fitting approach to track-before-detect. Recent comparisons have shown that it can give performance close to numerical approximations to the optimal Bayesian filter at a fraction of the computation cost. The derivation of H-PMHT makes no explicit assumption about the target process model or the sensor point spread...
In this paper we evaluate the effects of physically plausible renderings of ground truth sequences for optical flow estimation, as it seems to be a common belief that real world effects such as specular highlights, shadows, etc. cannot easily be reproduced synthetically while their influence on optical flow is hard to classify. Therefore, a real sequence with shadows and specular reflections was recorded...
Image fusion is an important visualization technique of integrating coherent spatial and temporal information into a compact form. Laplacian fusion is a process that combines regions of images from different sources into a single fused image based on a salience selection rule for each region. In this paper, we proposed an algorithmic approach using a mask pyramid to better localize the selection process...
The Gaussian Mixture Model (GMM) is one of the most widely used models for statistical segmentation of brain Magnetic Resonance (MR) images. Because the GMM is a histogram-based model, has an intrinsic limitation which spatial information is not included. This problem causes the GMM to make good results only on images with low levels of noise and high level of contrast. In this paper, an automated...
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