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We discuss the performance of a set of local transform domain filters, with respect to varying parameters. We perform Monte Carlo simulations of the filters over five different test images at different noise levels, and evaluate how much the selection of filter parameters affect the filter performance and how far their performances are from that of the ideal Wiener filter.
Probability Density Functions defined on IR+ can be successfully modeled with the help of the Mellin Transform : this rather underrated transform is well suited for such functions so that we propose the new definitions of "second kind" characteristic functions based on this transform. By this way, second kind moments and second kind cumulants can also be defined, so that multiplicative noise,...
This paper introduces an efficient approach towards blind deblurring of palm print images suffered from severe motion blur. First an improved Hough transform method is proposed to detect the blur angle and length of palm print image accurately. Analysis of blurred image is performed in Fourier domain which contains important information about the blur orientation of an image. After detecting the blur...
Removing noise, called denoising, is an essential factor for achieving the intuitive and accurate results in boundary image matching. This paper deals with a partial denoising problem that tries to allow a limited amount of noise embedded in boundary images. To solve this problem, we first define partial denoising time-series that can be generated from an original image time-series by removing a variety...
The recent trend of proliferation of road accidents and fatalities, calls for a methodology that can appease the burden on the drivers during certain crucial moments, requiring fast response and decision making. This paper expatiates a novel and effective procedure for determining the steering angle required to keep the vehicle in the middle of the lane. The procedure used is divided in multiple stages...
This paper addresses the issue of magnetic resonance (MR) Image reconstruction at compressive sampling (or compressed sensing) paradigm followed by its segmentation. To improve image reconstruction problem at low measurement space, weighted linear prediction and random noise injection at unobserved space are done first, followed by spatial domain de-noising through adaptive recursive filtering. Reconstructed...
Precise coronary artery segmentation is a prerequisite for quantitatively assessing the severity of coronary artery stenosis. Extracting the centre line of the 3D volumetric coronary artery tree, also named as 3D skeletonization, plays an important role in identify the variations of cross-sectional profile. Typically there are three skeletonization methods, viz. distance transformation, Voronoi method...
In this paper, we propose a feature-based approach to address the challenging task of recognising overlapping sound events from single channel audio. Our approach is based on our previous work on Local Spectrogram Features (LSFs), where we combined a local spectral representation of the spectrogram with the Generalised Hough Transform (GHT) voting system for recognition. Here we propose to take the...
The objective of copy-move forgery detection methods are to find copied regions within the same image. There are two main approaches to detect copy-move forgery: keypoint-based and block-based methods. Although the former is superior in terms of computational complexity, these methods neglect the smooth regions since they confine their search to salient points. On the other hand, while block-based...
Poly Cystic Ovary Syndrome (PCOS) is an endocrine disorder affecting many women in their reproductive age groups related with these problems of infertility, diabetes mellitus and cardiovascular disease. Diagnosis of the condition is mostly done by imaging parameters. Ultrasound imaging has become a very important technology in diagnosis of PCOS. Due to overlapping of the follicles, inherent noise...
The ability to simplify and categorize things is one of the most important elements of human thought, understanding, and learning. The corresponding explorative data analysis techniques -- dimensionality reduction and clustering -- have initially been studied by our community as two separate research topics. Later algorithms like CLIQUE, ORCLUS, 4C, etc. Performed clustering and dimensionality reduction...
Over the past few decades, a considerable amount of literature has been published on shape classification. Since classification of well-segmented shapes has become easy to achieve, a number of recent studies have emphasized the importance of robustness to noise and deformations. So in this paper, we undertake the task of classifying similar & noisy binary shape images, using a biologically inspired...
The presence of parasite interference signals could cause serious problems in the registration of ECG signals and many works have been done to suppress these noise signals. By conducting a mathematical method based on varying window length as according to the distance from the adjacent Rpeak which are assumed to be high frequency noise (power line interference, electromyography noise) is removed with...
This paper presents a robust watermarking for still digital images based on Fast Walsh-Hadamard Transform (FWHT) and Singular Value Decomposition (SVD) using Zigzag scanning. In this paper, after applying Fast Walsh-Hadamard transform to the whole cover image, the Walsh-Hadamard coefficients are arranged in zigzag order and mapped into four quadrants-Q1, Q2, Q3, Q4. These four quadrants represent...
Noisy whisper contaminated by different types of noise are enhanced by compressive sensing method. The intelligibility performance of the enhanced whisper is measured using the short time objective index (STOI). To assess the effect of spectra density on compressive sensing, the real-valued discrete Gabor transform is used to transform the noisy whisper into the time-frequency domain. Experimental...
Extracting Linear Features from Microwave Images (SAR) using Beamlet Transform is proposed in this paper. Microwave images are independent of climate. In certain durations these images are affected by noise (Speckle). So Speckle is removed in this work by using Soft threshold technique. For extracting the linear Features, Beamlet Transform based algorithm was applied. This algorithm recursively partitions...
Recently, two-dimensional canonical correlation analysis (2DCCA) proved to be an efficient technique for image feature extraction. In this paper we present a method of 2DCCA with probabilistic framework called probabilistic 2DCCA (P2DCCA), which is robust to noise and is able to cope with missing data problems. The experimental recognition results on three subsets of AR face database show the robustness...
This study attempts to establish methods for characterizing the complexity of ordinal data through the information and entropy parameters. In this respect, there were examined the methods for measuring the complexity of data with similar statistical characteristics and the parameters that can make the difference between them were established. For this purpose, the analysis was applied to three data...
In this paper an efficient denoising technique is introduced for removal of noise from digital images by combining filtering in both the domains, the wavelet and the spatial domain. Here AWGN noise is under considered and treated as a Gaussian random variable. In this work the proper orthogonal decomposition (POD) is applied in wavelet domain which spreads the energy of the signal in to a few principal...
This paper describes design considerations for acquiring improved performance on a new type of display system for regenerating three-dimensional images with an invisible high-frequency code pattern whose attribute depends on the depth of object. Three-dimensional images to be demonstrated on the new 3D image display system will be generated in the following 3 steps: That is; firstly embedding data...
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