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The proper segmentation of the vascular system of the retina currently attracts wide interest. As a precious outcome, a successful segmentation may lead to the improvement of automatic screening systems. Namely, the detection of the vessels helps the localization of other anatomical parts and lesions besides the vascular disorders. In this paper, we recommend a novel approach for the segmentation...
We propose a gradient estimation algorithm in a color filter array (CFA) image and apply it to demosaicing. Using directly computed ones, the proposed method estimates gradients, which cannot be computed directly from the CFA image. The proposed gradient estimation method is simple, improving the performance of existing demosaicing methods.
Road region is an important information for guidance of such objects like robots or autonomous vehicles. The goal of this research is to develop a robust monocular algorithm for extraction of road region from image sequences, captured by camera mounted on the moving objects. The key idea introduced in the first stage of this research is to express the road region in terms of probability density function...
Image matting is an important task in image and video editing. In this paper we propose a novel matting system, which can provide good results with less human intervention. We split the task into two steps: attention-based scribble extraction followed by alpha matting. We use the attention shift trace which is refined in the HSI color space as the useful constraints for matting algorithm instead of...
This paper proposes an automatic color transfer method for processing images with complex content based on intrinsic component. Although several automatic color transfer methods has been proposed by including region information and/or using multiple references, these methods tend to become ineffective when processing images with complex content and lighting variation. In this paper, our goal is to...
This paper proposes a nonparametric saliency model based on kernel density estimation (KDE) mainly aiming at content-based applications such as salient object segmentation. A set of KDE models are constructed on the basis of regions segmented using the mean shift algorithm. For each pixel, a set of color likelihood measures to all KDE models are calculated, and then the color saliency and spatial...
This paper presents a novel denoising algorithm for color images. It is difficult to reduce color noise at high speed without losing image details. To solve this problem, the proposed method employs maximum a posteriori (MAP) estimation based on a Gaussian model in ε-neighborhood of the pixel and CIELAB color space. Using the correlation between RGB components in ε-neighborhood, color noise is reduced...
Color Filter Array (CFA) interpolation is an integral part of image processing pipeline for single sensor digital cameras. Many CFA algorithms have been proposed over the years to improve resulting image quality. One such algorithm is the highly successful Directional Linear Minimum Mean-Square Error Estimation (DLMMSE) method. We make several observations on this algorithm and propose a new method...
Planes are important geometric features and can be used in a wide range of vision tasks like scene reconstruction, path planning and robot navigation. This work aims to illustrate a plane segmentation system based on homography computation and optical flow estimation. Firstly, using two image frames from a monocular sequence, a set of match pairs of interest points is obtained. An algorithm was developed...
We consider a simple statistical model of the image, in which the image is represented as a sum of two parts: one part is explained by an i.i.d. color Gaussian mixture and the other part by a (piecewise-) smooth gray scale shading function. The smoothness is ensured by a quadratic (Tikhonov) or total variation regularization. We derive an EM algorithm to estimate simultaneously the parameters of the...
We propose a method for estimating demosaicing algorithms from image noise variance. We show that the noise variance in interpolated pixels becomes smaller than that of directly observed pixels without interpolation. Our method capitalizes on the spatial variation of image noise variance in demosaiced images to estimate the color filter array patterns and demosaicing algorithms. We verify the effectiveness...
We present a novel segment extraction and segment-based depth estimation technique. Proposed segment extraction technique exploits depth and motion information of segments between frames as well as color information. We firstly divide each frame of reference view into foreground and background areas based on initial depth information obtained from time-of-flight (TOF) camera. Then we extract segments...
In this paper we describe a novel approach to autonomous dirt road following. The algorithm is able to recognize highly curved roads in cluttered color images quite often appearing in offroad scenarios. To cope with large curvatures we apply gaze control and model the road using two different clothoid segments. A Particle Filter incorporating edge and color intensity information is used to simultaneously...
This paper presents a novel dense disparity estimation method using phase matching and color segmentation. In the proposed method, the initial disparity map is firstly obtained by an improved phase-based stereo matching solution. The solution effectively restrains two tough problems of phase singularities and phase wrap, in a coarse-to-fine approach, by using Dual-Tree Complex Wavelet Transform (DT...
This paper presents an in-vehicle monocular road detection system. The system acquires color images in the input and uses image processing techniques to boost robustness of this algorithm that it is possible to improve it's autonomy and "intelligence" in segmentation of driving space in different road scenes. The road detection algorithm consists of two main steps: vanishing point estimation...
In this paper we present a segmentation system for monocular video sequences with static camera that aims at foreground/background separation and tracking. We propose to combine a simple pixel-wise model for the background with a general purpose region based model for the foreground. The background is modeled using one Gaussian per pixel, thus achieving a precise and easy to update model. The foreground...
3D technologies are becoming the more and more relevant in recent years. Visual communications, as well as image and video analysis, benefit in great manner from spatial information such as depth for various applications. Highly accurate visual depth estimation often involves complex optimization algorithms in order to fit proper estimation models to data. From a stereo/multiview matching perspective,...
Most algorithms for extracting illuminant chromaticity from arbitrary images, such as the images found on the web, are based on machine learning techniques. We will show how a physics-based methodology can be adapted to provide relative illumination information on real images. More specifically, we use the inverse-intensity chromaticity representation and show how the analysis of the histograms of...
This paper proposes an automatic color transfer method based on multi-reference and graph-theoretic region correspondence estimation. When multiple high-quality reference images are available, our goal is to determine a set of best reference colors for transferring the color characteristics of the target image. Given a target image, we first employ content-based image retrieval technique to obtain...
Parametric density estimation is widely used to solve many image processing problems. We examined the parametric estimation using linear combination of 1D Gaussians in many works. In this work, we extend our model to estimate density of the colors in color images. We approximate the marginal density of each class in the empirical probability density function by a 3D Gaussian distribution. Then, the...
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