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An important problem in image smoothing is to reduce noise while preserving sharp edges. In this paper we extend the bilateral filter for better impulse noise suppression and near edge artifacts avoidance. The proposed method weights each pixel prior to bilateral filtering by an extra coefficient that is dependent on a noisiness measurement. Consequently, the influence of noisy pixels can be significantly...
For intelligent vehicle systems, lane detection is still a challenging task because it must cope with various road environments. In this paper, we propose a reliable method with Gabor filters. The proposed approach consists of two step. In the first step, the vanishing-point locations is estimated by the texture feature based method. The key attributes of this method consist of the dominant texture...
This paper will be shown the problem and solve of the image interpolation by the directional inverse distance weighting (IDW). The anti-alias method which is the blurring kernel is used for solving on the IDW method. The problem of this method has occurred after this method is processed finish. The experiment results are shown the better performance than the conventional method.
Design of a computer-aided automatic system is very important for identification of different ocular diseases. A vital concern within this framework is the accurate retinal blood vessel extraction. This paper extracts vessels using curvelet transform, morphological operation, matched filtering and Differential Evolution based optimal clustering. Curvelet transform is implemented to enhance vessel...
Image scaling is one of the widely used techniques in various portable devices to fit the image in their respective displays. Traditional image scaling architectures consume more power and hardware, making them inefficient for use in portable devices. In this paper, a low complexity image scaling algorithm is proposed. In the proposed algorithm, the target pixel is computed either by bilinear interpolation...
An image restoration scheme using frequency domain estimation to counter the motion blur effect is presented. The blurring process is characterized as a point spread function (PSF), which is further decomposed to a defocusing kernel and a motion kernel. The defocusing kernel, modeled as a Gaussian function, is estimated in the spatial domain while the motion kernel estimation is performed in the frequency...
The real-time information on the Web changes dynamically and surge quickly, which cause considerable difficulty in access to interested information. How to mine hot events, how to analyze the correlation of events and how to organize information structurally are challenging tasks. In this paper, to address these problems, we propose STeller, an approach to mine context-aware story — a series of correlated...
Aggressive Optical Proximity Correction (OPC) has been widely adopted in optical lithography to preserve circuit performance for sub-20nm technology nodes. However, complex mask patterns are output resulting in lower mask manufacturability and large computational time. In this paper, we propose a fast OPC algorithm in which intensity estimation during OPC is improved for better pattern fidelity and...
Foreground Detection is one of the critical parts in the field of Computer Vision that aims to identify changes in the image sequences and to separate the foreground image from their background image. It is an arrangement of systems that typically examine the video sequences progressively and are recorded with a stationary camera. To detect brain tissue at early stage, a robotized framework utilizing...
Single image super resolution requires approximation of high frequency information that was not captured in the available low resolution image. The process may result in an image that differs significantly from the original scene if no constraints are imposed. Iterative back-projection is one method used to guide the resolution enhancement process. This paper augments the iterative back-projection...
In nanocrystallography, diffraction images are captured to gain insights into the structure of macromolecules. A new generation of experiments is able to take a vast amount of images in a short time. However, most of the images are not suitable for further research. It is not feasible to store and process all images in a reasonable amount of time. In previous work we proposed algorithms able to distinguish...
Image processing is a major aspect in transmission of data in compact fashion without loss of information. There are several algorithms defined for image compression, edge detection and noise reduction which form image transformation techniques. The proposed paper focuses on edge detection of given image using kernel matrix using sliding window algorithm. The interface system includes FPGA and beagle...
In the recent history, kernel methods had established themselves as powerful tools for computer vision. In this paper we introduce an integer image kernel function based on Ramanujan Sums which finds its place in image vision. The paper proves the validity of kernel function theoretically and also shows the application of the kernel in image vision. Ramanujan Sums are based on number theory and hence...
Image filtering is a process of reducing noise which degrades the performance of image processing. In some applications such as segmentation or classification, denoising has been designed to smooth the homogeneous areas while keeping and enhancing the edges. In several applications such as video analysis, image-guided surgical interventions or visual servoing, real-time denoising is needed. The devoted...
Edge detection is one of the most important paradigm of Image processing. Images contain millions of pixel and each pixel information is independent of its neighbouring pixel. Hence this paper puts to test the capability of Graphics Processing Unit (GPU) to compute in parallel against the millions of pixel calculations involved in image processing. Each pixel operation is independent from other thus...
This article reviews and discusses the fuzzy system implementation as an efficient edges detector for the image. Authors that suggested this method used different ways to feed the fuzzy system and different membership functions that depend on the characteristics of the data input. Some techniques feed the data directly with a 2×2 or 3×3 window others process the data with filters before feeding the...
This paper proposes a robust blind deconvolution method for removing a uniform blur from microscopy images. For the estimation of the kernel — point spread function (PSF) — the stable edge is estimated using a fuzzy edge prediction method. Based on the estimated stable edges, optimizing a blurring objective function leads to a closed form for the estimation of a kernel and latent image. In comparison...
This paper proposes the exploration of approximate adders for the implementation of power-efficient Gaussian and Gradient filters for Image Processing. The Gaussian filter is a convolution operator which is used to blur images and to remove noise. On the other hand, the Gradient of an image measures how it is changing. Both blocks can be designed in hardware using only shifts and additions. In this...
Blind deconvolution refers to a class of problems of recovering a sharp version of a blurred image without any information about the blur kernel. In this paper, we propose a novel approach for blind deconvolution based on differential evolution (DE) algorithm, which is arguably one of the most powerful stochastic real-parameter optimization algorithms. Thanks to DE algorithm, various non-conjugate...
Trilateral filtering presents an edge preserving smoothing filter. The predecessor of Trilateral filtering, the bilateral filter is a non-linear filtering technique that can reduce noise from an image while preserving the strong and sharp edges, but it cannot provide desired result when the edges have valley or ridge like features. The Trilateral filter is extended to be a gradient-preserving filter,...
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