Showing papers on "Edge enhancement published in 2008"

Edge enhancement of potential-field data using normalized statistics

Abstract: Edge enhancement in potential-field data helps geologic interpretation. There are many methods for enhancing edges, most of which are high-pass filters based on the horizontal or vertical derivatives of the field. Normalized standard deviation (NSTD), a new edge-detection filter, is based on ratios of the windowed standard deviation of derivatives of the field. NSTD is demonstrated using aeromagnetic data from Australia and gravity data from South Africa. Compared with other filters, the NSTD filter produces more detailed results.

Edge Enhancement Nucleus and Cytoplast Contour Detector of Cervical Smear Images

Abstract: This paper presents an edge enhancement nucleus and cytoplast contour (EENCC) detector to enable cutting the nucleus and cytoplast from a cervical smear cell image. To clean up noises from an image, this paper proposes a trim-meaning filter that can effectively remove impulse and Gaussian noises but still preserves the sharpness of object boundaries. In addition, a bigroup enhancer is proposed to make a clear-cut separation of the pixels lying in-between two objects. A mean vector difference enhancer is presented to suppress the gradients of noises and also to brighten the gradients of object contours. What is more, a relative-distance-error measure is put forward to evaluate the segmentation error between the extracted and target object contours. The experimental results show that all the aforementioned techniques proposed have performed impressively. Other than for cervical smear images, these proposed techniques can also be utilized in object segmentation of other images.

Efficient video text detection using edge features

Abstract: In this paper, we explore new edge features such as straightness for the elimination of non significant edges from the segmented text portion of a video frame to detect accurate boundary of the text lines in video images. To segment the complete text portions, the method introduces candidate text block selection from a given image. Heuristic rules are formed based on combination of filters and edge analysis for identifying a candidate text block in the image. Furthermore, the same rules are extended to grow boundary of candidate text block in order to segment complete text portions in the image. The experimental results of the proposed method show that the method outperforms an existing method in terms of a number of metrics.

Sub-pixel data fusion and edge-enhanced distance refinement for 2D/3D images

Abstract: An important field of research in computer vision is the 3D analysis and reconstruction of objects and scenes. A rather new technology in this context is the Photonic Mixer Device (PMD), based on the Time-Of-Flight principle, which measures full-range distance information in real-time. Unfortunately, PMD-based devices have still limited resolution and provide only IR intensity information. This paper describes a fast algorithmic approach to combine high resolution colour images with PMD distance data, acquired using a binocular camera set-up. The resulting combined RGBZ-data not only enhances the visual result, but also represents a basis for advanced data processing, e.g. object recognition with sub-pixel accuracy. A simple but efficient method is used to detect geometric occlusion caused by the binocular set-up, which otherwise will lead to false colour assignments. Additionally, we introduce an enhanced filtering technique used for the edge-enhanced distance refinement of the geometry provided by the PMD camera. The technique incorporates a proper handling of boundaries and an iterative refinement approach, which can be used to enhance the 2D/3D-fusion accuracy.

Transductive object cutout

Abstract: In this paper, we address the issue of transducing the object cutout model from an example image to novel image instances. We observe that although object and background are very likely to contain similar colors in natural images, it is much less probable that they share similar color configurations. Motivated by this observation, we propose a local color pattern model to characterize the color configuration in a robust way. Additionally, we propose an edge profile model to modulate the contrast of the image, which enhances edges along object boundaries and attenuates edges inside object or background. The local color pattern model and edge model are integrated in a graph-cut framework. Higher accuracy and improved robustness of the proposed method are demonstrated through experimental comparison with state-of-the-art algorithms.

2D to 3D convertion based on edge defocus and segmentation

Abstract: This paper presents a depth estimation method which converts two-dimensional images into three-dimensional data. Based on two-dimensional wavelet analysis of Lipschitz regularity for defocus estimation on edges, this method can effectively eliminate the horizontal stripes in the depth map resulted from traditional one-dimensional wavelet based approaches. Besides, we also propose several techniques such as edge enhancement, color-based segmentation, and depth optimization to obtain a more reliable and smoother depth map. The experimental results demonstrate the effectiveness of our proposed techniques.

Medical image enhancement using threshold decomposition driven adaptive morphological filter

Abstract: One of the most common degradations in medical images is their poor contrast quality. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image. In this paper, a new edge detected morphological filter is proposed to sharpen digital medical images. This is done by detecting the positions of the edges and then applying a class of morphological filtering. Motivated by the success of threshold decomposition, gradient-based operators are used to detect the locations of the edges. A morphological filter is used to sharpen these detected edges. Experimental results demonstrate that the detected edge deblurring filter improved the visibility and perceptibility of various embedded structures in digital medical images. Moreover, the performance of the proposed filter is superior to that of other sharpener-type filters.

Patterns of throughfall deposition along a transect in forest edges of silver birch and Corsican pine

Abstract: In two adjacent forest stands in Flanders, one dominated by Corsican pine (Pinus nigra subsp. laricio Maire) and another dominated by silver birch (Betula pendula Roth), throughfall deposition was monitored along a transect per- pendicular to the forest edge exposed to the prevailing wind direction. Throughfall deposition of Na + ,K + ,C a 2+ ,M g 2+ , NH4 + ,N O3 - ,C l - , and SO4 2- was examined on forest edge patterns expressed in the depth of influence of the edge effect (forest edge distance) and the level of enhancement at the edge (forest edge enhancement). In addition, an integrated forest edge enhancement factor was computed that incorporates these two parameters. Our results show that the edge effects on throughfall deposition of Na + ,C l - , the sum of so-called base cations, the sum of potentially acidifying ions, and the sum of inorganic nitrogen (NH4 + +N O3 - ) are more pronounced in the pine stand. The edge zone of the pine stand receives as a result of the edge effect 9.4 times more extra potentially acidifying ions and 12.7 times more extra inorganic nitrogen than the birch stand. We conclude that an appropriate design or conversion of the edge structure, from high-density Corsi- can pine plantations into lower density deciduous forests, can reduce the input of acidifying and eutrophying pollutants in the forest edge.

Filter assembly and image enhancement system for a surveillance camera and method of using the same

Abstract: A filter assembly adapted to be used with a camera for selectively controlling the light that reaches the camera's aperture In one embodiment, the filter assembly comprises three filters adapted to be independently moved between a first position wherein they are not in front of the camera's aperture and a second position wherein they are in front of the camera's aperture The first and second filters are polarizing filters adapted to block portions of visible light The third filter is an infrared filter adapted to block infrared light In addition to moving between its first position and its second position, the second filter is also adapted to rotate up to 360 degrees The image captured by the camera may be improved using a computer implemented image enhancement system that uses one or more of multi-spectral imaging, deconvolution, edge enhancement, and dynamic range translation

Edge Detection in Grayscale, Color, and Range Images

Abstract: Edges are commonly defined as significant local changes in an image Edge provides an indication of the physical extent of objects in the image Edge detection is viewed as an information reduction process that provides boundary information of regions by filtering out unnecessary information for the next steps of processes in a computer vision system Thus, edge detection is one of the most essential steps for extracting structural features for human and machine perception The success of high-level computer vision processes heavily relies on the good output from the lower level processes such as edge detection Many edge detection algorithms have been proposed in the last 50 years This article presents the fundamental theories and the important edge detection techniques for grayscale, color, and range images Keywords: edge; gradient; Sobel edge; Laplacian; Laplacian of gaussian; Canny edge; Cumani operator; roof edge; normal changes

Constrained Unsharp Masking for Image Enhancement

Abstract: In this paper we present a cost-effective solution for combined de-noising and sharpening of digital images. Our method combines the unsharp masking and sigma filtering techniques through a regularization mechanism thus ensuring effective noise reduction and edge enhancement in the processed image. We describe our method in detail and we analyze the proposed implementation through extensive experiments done in various scenarios. Due to its low computational complexity the proposed method is well suited for mobile implementations.

Image processor and image processing program

Abstract: The digital camera ( 100 ) has an image processor that corrects an input image for a spatial frequency band. The edge enhancement block ( 106 ) computes an edge component for band correction. A signal interpolated at color interpolation block ( 107 ) to make compensation for a color component missing from each pixel of a single-chip image is then converted at YC transform block ( 108 ) into a luminance signal and a color difference signal after tone correction, the luminance and color signals sent out to YC synthesis block ( 110 ) and color saturation correction block ( 109 ), respectively. Then, the color saturation correction block ( 109 ) controls the color saturation of the color difference signal to send it out to YC synthesis block ( 110 ). At the same time, the edge component computed at edge enhancement block ( 106 ) is sent out to YC synthesis block ( 110 ), too.

A Robust Edge Enhancement Approach for Low Vision Patients Using Scene Simplification

Abstract: Patients with low vision have reduced visual acuity and a significant loss of contrast sensitivity resulting in gross blurring of the visual scene over a significant area of their field of view. This paper describes a robust approach for edge enhancement for visual impairments patients, based on simplifying the visual scene to remove unnecessary textures and then enhance the edges of the simplified image. The effectiveness of this scheme was demonstrated in a pilot study composed of three patients suffering from macular degeneration. They succeeded to identify most of the objects in the images when using our robust enhancement compared to the original images.

Image processing system, image processing method, and image processing program product

Abstract: An image processing system including: a CCD which outputs an image signal; an edge extraction unit which extracts an edge signal from the image signal; a false edge estimation unit which estimates an edge signal that arises due to noise components based upon the image signal; an edge correction unit which corrects the edge signal by performing coring processing based upon the edge signal that arises due to noise components; and an edge enhancement unit which performs enhancement processing on the image signal based upon the edge signal thus corrected.

Perceptually relevant ringing region detection method

Abstract: A novel approach towards automatic detection of perceived ringing regions is presented. The algorithm takes into account both the physical structure and the human visual perception of the ringing artifacts. All perceived ringing regions are explicitly captured by means of a newly proposed edge detector, followed by an efficient analysis of ringing visibility around each detected edge segment. Determining visibility is based on luminance masking and texture masking as typical for the human visual system. The proposed detection method is validated by comparing its performance with the ringing regions resulting from a psychovisual experiment.

Image processing system, image processing method, and computer program product

Abstract: An image processing system includes a multiresolution decomposition section for frequency decomposing an image signal into high and low frequency components at an nth stage, a correction coefficient calculation section for calculating at least one of a gradation correction coefficient, a noise correction coefficient, and an edge correction coefficient with respect to the high frequency component at an ith decomposition stage (1≦i≦n) based on at least one of the low frequency component at the ith decomposition stage, a visual system adaptation model, a noise amount estimation model, and an edge enhancement model, a correction section for correcting the high frequency component based on the calculated correction coefficient, and a multiresolution composition section for composing the image signal corrected based on the low frequency component and the corrected high frequency component.

Image pickup apparatus and method

Abstract: A digital still camera includes a lens system. A cold mirror separates object light incident on the lens system into a visible light component and an infrared component. A visible light image sensor outputs a first image signal of a visible light image by receiving the visible light component. An infrared light image sensor outputs a second image signal of an infrared image by receiving the infrared component. A contour signal generator extracts a high frequency component from a luminance signal determined according to the second image signal, to produce an edge enhancement signal. An adder adds the edge enhancement signal to a luminance signal determined according to the first image signal. Addition of the edge enhancement signal is adapted to the object light from an object at a far distance. Specifically, the cold mirror reflects the visible light component and transmits the infrared component.

Satellite Image Enhancement by Controlled Statistical Differentiation

Abstract: This paper presents a new method of statistical differencing for the enhancement of contrast images. Our approach controls the sharpening effect using two constants in such a way, that enhancement occurs in intensity edges areas and very little in uniform areas. It has been proven that our method is superior to similar existent and can be applied to pre-process satellite images.

Fast image super-resolution using Connected Component enhancement

Abstract: The paper focuses on reconstructing the discontinuity between homogenous color regions in an interpolated image to improve its perceptual quality. A low-resolution input image is firstly interpolated and then decomposed into several patches. Each patch is then segmented into multiple homogenous regions using connected component analysis technique. Then a spatial-filter is applied to enhance the color/intensity transition between neighboring components. The designed spatial-filter combines the advantages of both bilateral-filtering and unsharp masking methods, with high computational efficiency. The proposed method can be used for image/video super-resolution applications. Experimental results are promising.

Investigation of physical image characteristics and phenomenon of edge enhancement by phase contrast using equipment typical for mammography.

Abstract: A technique called phase contrast mammography PCM has only recently been applied in clinical examination. In this application, PCM images are acquired at a 1.75 magnification using an x-ray tube for clinical use, and then reduced to the real size of the object by image processing. The images showed enhanced object edges; reportedly, this enhancement occurred because of the refraction of x rays through a cylindrical object. The authors measured the physical image characteristics of PCM to compare the image characteristics of PCM with those of conventional mammography. More specifically, they measured the object-edge-response characteristics and the noise characteristics in the spatial frequency domain. The results revealed that the edge-response characteristics of PCM outperformed those of conventional mammography. In addition, the characteristics changed with the object-placement conditions and the object shapes. The noise characteristics of PCM were better than those of conventional mammography. Subsequently, to verify why object edges were enhanced in PCM images, the authors simulated image profiles that would be obtained if the x rays were refracted and totally reflected by using not only a cylindrical substance but also a planar substance as the object. So, they confirmed that the object edges in PCM images were enhanced because x rays were refracted irrespective of the object shapes. Further, they found that the edge enhancements depended on the object shapes and positions. It was also proposed that the larger magnification than 1.75 in the commercialized system might be more suitable for PCM. Finally, the authors investigated phase-contrast effects to breast tissues by the simulation and demonstrated that PCM would be helpful in the diagnoses of mammography. © 2008 American Association of Physicists in Medicine. DOI: 10.1118/1.2968091

Adaptive Anisotropic Diffusion for Ultrasonic Image Denoising and Edge Enhancement

Abstract: Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme. Keywords—anisotropic diffusion, coordinate transformation, directional derivatives, edge enhancement, hyperbolic tangent function, image denoising.

Edge Detection of Image on the Local Feature

Abstract: The traditional methods of image edge detection are sensitive to the noise comparatively and can not locate the edge exactly. Aiming at the shortage of the traditional methods of image edge detection, the paper puts forward the edge detection of the low signal noise ratio image (the low SNR image) according to the local feature. Firstly, we analyze the relationship of the neighborhood of pixels and introduce the function expression which is used to estimate whether the pixel is on the image edge or not. The method takes the pixel as the research object, and the edge to be detected is perhaps the noise or just itself. According to the edge's continuity of the image and the isolation of noise, we use the morphology to extract the image edge and overcome the noise effect on the edge, then use the morphological gradient to eliminate the false edge points. With the new method, the image edge can be detected more correctly.

Improved algorithm for Sobel edge detection of image

Abstract: Edge detection is used in image processing and computer vision. The typical Sobel edge detection algorithm in the digital image processing was analyzed. An improved algorithm for the image edge detection based on Sobel algorithm was proposed to overcome the disadvantages, which the obtained edges of the image is thick and sensitive to the noise. The edge types that exist in the real images are described with mathematical models and the models of the continuous edges are regarded as a research subject. A template for detecting the direction of the image edges was rebuilt. The thinning processing for the gradient histograms of images was adopted, to improve the low accuracy of locating the edge position, caused by the traditional Sobel edge detection which was based on oneorder derivative′s maximum value or two-order derivative′s zero-crossing. The simulated result shows that the algorithm has a better immunity to the noise jamming of images and the edge position extracted by the algorithm is accurate.

An application of fuzzy morphology for enhancement of aerial images

Abstract: This paper proposes an approach for structure based separation of image objects using fuzzy morphology for aerial images With set operators in fuzzy context, we apply an adaptive alpha-cut morphological processing for edge detection and image enhancement A Top-hat transform is first applied to the input image and the resulting image is thresholded to a binary form The image is then thinned using hit-or-miss transform Finally, m-connectivity is used to keep the desired number of connected pixels The output image is overlaid on the original for enhanced boundaries Experiments were performed on a variety of aerial images A comparison to other edge enhancement techniques like Sobel Log and Canny filtering shows improved performance by the proposed technique

Analysis and Research of Image Edge Detection Methods

Abstract: The edge is an important signature of an image. The edge detection plays an important role in computer vision and image analysis and is also a basic and difficult problem in image target detection. In this paper, the conventional edge detection methods and their features are analyzed and these methods are used to process the original images and noise images respectively.The processing results show that the operators such as Sobel, Roberts, Prewitt, Kitsch and LOG have their advantages and disadvantages, and their location precision, noise sensitivity and complexity are restrained one another.

ROI processing for visual features extraction in lip-reading

Abstract: Region of interest (ROI) is the key basis of visual features extraction in lip-reading process. In this paper, we discussed the ROI processing method and explored its impact on recognition accuracy with the comparison of four kinds of processed ROIs obtained by using four basic image processing methods: gray-scale normalization, difference enhancement, edge enhancement and image segmentation. Then recognition tasks for speaker-independent lip-reading were carried out by the aid of continuous hidden Markov model (CHMM). The experimental results show that for discrete cosine transform (DCT) based features, normalized gray-scale image can achieve the best recognition performance among these four ROIs.

Method of Image Edge Enhancement

Abstract: A method of image edge enhancement comprises: determining the edge trend for an image in accordance with the second order gradient value of a center pixel in different directions; performing interpolation operation with the center pixel; calculating absent color component of pixels; performing edge enhancement for the image in the interpolation module in accordance with original color component of the center pixel and the image edge trend based on the Bayer data. The image edge enhancement process takes into account the influence of the green component values of different pixels surrounding the center pixel, and adopts a noise-resistant, self-adaptive edge enhancement algorithm, to suppress noise on the image edge. Thus, the resulting image has a clear image edge. In addition, the fact that the process performs image edge enhancement in the interpolation module based on the Bayer data can significantly reduce the consumption of memory space.

Anniversary paper: image processing and manipulation through the pages of Medical Physics.

Abstract: The language of radiology has gradually evolved from “the film” (the foundation of radiology since Wilhelm Roentgen’s 1895 discovery of x-rays) to “the image,” an electronic manifestation of a radiologic examination that exists within the bits and bytes of a computer. Rather than simply storing and displaying radiologic images in a static manner, the computational power of the computer may be used to enhance a radiologist’s ability to visually extract information from the image through image processing and image manipulation algorithms. Image processing tools provide a broad spectrum of opportunities for image enhancement. Gray-level manipulations such as histogram equalization, spatial alterations such as geometric distortion correction, preprocessing operations such as edge enhancement, and enhanced radiography techniques such as temporal subtraction provide powerful methods to improve the diagnostic quality of an image or to enhance structures of interest within an image. Furthermore, these image processing algorithms provide the building blocks of more advanced computer vision methods. The prominent role of medical physicists and the AAPM in the advancement of medical image processing methods, and in the establishment of the “image” as the fundamental entity in radiology and radiation oncology, has been captured in 35 volumes of Medical Physics .

A Novel Edge Enhancement Method for Ultrasound Imaging

Abstract: One of the most important problems in ultrasound image processing is to find the edges of structures and enhance weak borders between different organs. In this paper, we propose an algorithm that detects and enhances edges adaptively based on local histogram distribution. From the local histogram distribution we can get the "local histogram range image (LHRI)". On the basis of this image we apply an adaptive edge enhancement method to process ultrasound image. We find that the detection technique performs well, edges and borders are then enhanced by the enhance algorithm according to LHRI.