Showing papers on "Edge enhancement published in 1998"

Edge Detection Techniques-An Overview

Abstract: In computer vision and image processing, edge detection concerns the localization of significant variations of the grey level image and the identification of the physical phenomena that originated them. This information is very useful for applications in 3D reconstruction, motion, recognition, image enhancement and restoration, image registration, image compression, and so on. Usually, edge detection requires smoothing and differentiation of the image. Differentiation is an ill-conditioned problem and smoothing results in a loss of information. It is difficult to design a general edge detection algorithm which performs well in many contexts and captures the requirements of subsequent processing stages. Consequently, over the history of digital image processing a variety of edge detectors have been devised which differ in their mathematical and algorithmic properties. This paper is an account of the current state of our understanding of edge detection. We propose an overview of research in edge detection: edge definition, properties of detectors, the methodology of edge detection, the mutual influence between edges and detectors, and existing edge detectors and their implementation.

Analysis of the fractional Hilbert transform

Abstract: The Hilbert transform is of interest for image-processing applications because it forms an image that is edge enhanced relative to an input object. Recently a fractional Hilbert transform was introduced that can select which edges are enhanced and to what degree the edge enhancement occurs. Although experimental results of this selective edge enhancement were presented, there was no explanation of this phenomenon. We analyze a one-dimensional fractional Hilbert transform acting on a one-dimensional rectangle function and show how it produces an output image that is selectively edge enhanced.

POCS based adaptive image magnification

Abstract: We tackle the problem of magnifying an image without incurring blurring, ringing or other artifacts common to classical schemes. The proposed iterative scheme starts with an initial magnified image generated by a process of selective interpolation. By placing suitable constraints on the final magnified image, which are convex in nature, we show that magnification can be posed as a problem of finding a solution which lies at the intersection of convex sets. By avoiding explicit high frequency enhancing assumptions in the iterative process, we avoid edge enhancement artifacts in the magnified image.

Medical image enhancement method for hardcopy prints

Abstract: A method for the enhancement of medical images for hardcopy prints comprising the steps of: obtaining a medical image in digital format; conducting a plurality of operations for Human Visual System (HVS)-based edge enhancement with each operation having a uniquely specified high frequency amplification function and range such that edges are more enhanced in the shadow region than in the highlight region; adjusting image tone scale, for reflection prints increase the contrast in the shadow region and decrease the contrast in the highlight region, and for transparency prints decrease the contrast in the shadow region and increase the contrast in the highlight region; sending the processed image to the output device for hardcopy prints.

Time-domain image processing using dynamic holography

Abstract: Coded ultrafast optical pulses can be treated as one-dimensional (1-D) images in the time domain. We have converted spare-domain images into time-domain images using diffraction from dynamic holograms inside a Fourier pulse shaper, with photorefractive quantum wells (QW's) used as the dynamic holographic medium. We present several examples, in which amplitude or phase modulation of the hologram writing beams modifies the complex spectrum of the femtosecond output, resulting in a time-domain image. Both storage and processing of time-domain images can be achieved, depending on the hologram writing geometry and power densities. Time-domain processing operations such as edge enhancement, Fourier transform, and correlation are demonstrated.

Imaging apparatus with dynamic range expanded, a video camera including the same, and a method of generating a dynamic range expanded video signal

Abstract: An imaging circuit generates a first video signal with a first exposure interval and a second video signal with a second exposure interval substantially at the same time, the second exposure interval being shorter than the first exposure interval, the first and second video signals respectively having first and second dynamic ranges which are different but continues. The first video signal is synchronized with the second video signal. An exposure ratio between the first and second exposure intervals is detected. A gain of the second video signal is adjusted according to the exposure ratio. A combined video signal is generated from the first and second video signals according to a mixing control signal indicative of a mixing ratio between first and second video signals and levels of the first and second video signals to have an expanded dynamic range such that the first dynamic range is connected to the second dynamic range with difference in gains of the first and second video signals adjusted for linearity. An edge enhancement signal may be gain-controlled or coring-controlled according to the mixing control signal or the exposure ratio. The similar apparatus and method for color signals are also disclosed. The output dynamic range for a display is limited by a non-linear process.

Adaptive, quadratic preprocessing of document images for binarization

Abstract: This paper presents an adaptive algorithm for preprocessing document images prior to binarization in character recognition problems. Our method is similar in its approach to the blind adaptive equalization of binary communication channels. The adaptive filter utilizes a quadratic system model to provide edge enhancement for input images that have been corrupted by noise and other types of distortions during the scanning process. Experimental results demonstrating significant improvement in the quality of the binarized images over both direct binarization and a previously available preprocessing technique are also included.

Image edge enhancement with two cascaded acousto-optic cells with contrapropagating sound

Abstract: Basic real-time programmable image-processing operations are accomplished by use of acousto-optic (AO) cells. Instead of frequency-plane filters, the AO cells are placed directly behind the object. The one-dimensional edge-enhancement results with one AO cell can be improved by use of two AO cells that are placed in tandem with contrapropagating sound. The dominant second-derivative operation obtained from the transfer function of the undiffracted order works like a one-dimensional Laplacian operator that enables improved edge enhancement.

Method of display and control of adjustable parameters for a digital scanner device

Abstract: In a method for image processing, an image is scanned. A first portion of the image is displayed based at least in part upon a first value of a first adjustable parameter, where the first parameter affects the appearance of the image. A second portion of the image is simultaneously displayed based at least in part upon a second value of the first parameter, where the second value is different from the first value. A first processing value is selected based upon at least one of the first value and second value. The image is processed in accordance with the first processing value. In one aspect of the method, the first portion of the image is displayed adjacent to the second portion of the image. In another aspect of the method, the first parameter is selected from the group consisting of density, contrast, focus, edge enhancement, and gamma correction.

Edge enhancement of remote sensing image data in the DCT domain

Abstract: Edge Enhancement is an important image processing method for remote sensing image data. Many images are compressed by JPEG standard which uses the Discrete Cosine Transform (DCT). Manipulating data in the DCT domain is an efficient way to save the computer resources. In this paper, new algorithms for edge enhancement of remote sensing image data in the DCT domain are developed and implemented in three steps: highpass filtering, adding back full or part of gray levels to the original image, and linear contrast stretching. In addition, a method to approximate the minimum (MIN) and maximum (MAX) gray level intensity is presented in the paper, which are the necessary information for contrast stretching. Experimental results show that the quality of images generated by the new algorithms are comparable with that of images generated by the corresponding methods in the spatial domain.

Method and apparatus for image scaling using adaptive edge enhancement

Abstract: In an image scaling method and apparatus that uses adaptive edge enhancement, a plurality of sets of gradient threshold values and enhancement threshold values correspond respectively to predetermined enhancement modes. The enhancement mode corresponding to a mean pixel value for a one-dimensional pixel array that includes a center pixel to be updated and neighboring pixels of the center pixel is determined so that one of the sets of gradient threshold values and enhancement threshold values corresponding to the selected enhancement mode can be selected. After a sharpness value is computed by adding together absolute values of differences between values of the center pixel and each of the neighboring pixels, one of the enhancement threshold values in the selected set is selected by comparing the sharpness value with the gradient threshold values in the selected set. A sign of the selected enhancement threshold value is then determined such that difference between left side brightness and right side brightness is increased when the selected enhancement threshold value is added to the value of the center pixel.

Edge enhancement correction for improved image quality

Abstract: An objectionable outlining effect, seen as dark edges and white edges outlining everything in a scene, is eliminated by clipping or limiting the spikes generated by excessive enhancement. Specifically, a method is used for improving the quality of an enhanced video image, while simultaneously maintaining or improving image sharpness, by clipping the RGB levels of the enhanced video image, at the points of enhancement, to upper and lower level bounds representing the signal levels of the video signal prior to its enhancement.

Edge-enhancement processing apparatus and method, and medium containing edge-enhancement processing program

Abstract: An edge-enhancement processing apparatus which removes problems of the conventional edge enhancement processing, which requires checking by an operator's visual observation or a high-frequency band filter, thus complicating the construction. A computer main body 21, as the nucleus of edge enhancement processing, calculates an edge amount as change level while generating a vector based on the difference values of data between adjacent pixels, at step S 110, then selects and integrates edge amounts of only pixels having large edge amounts at steps S 120 and S 130, and obtains the mean value at step S 230, to obtain the sharpness level of the image while adding attention to the pixels having large image change levels. The computer main body 21 determines an edge enhancement level Eenhance based on the image sharpness level. Thus, the computer main body 21 automatically performs edge enhancement processing at an optimum enhancement level.

Edge enhancement by use of moving gratings in a bismuth silicon oxide crystal and its application to optical correlation

Abstract: The technique of moving gratings in a photorefractive crystal is applied to the edge enhancement of objects and edge-enhanced optical correlation. The nonlinear dependence of the optimum fringe velocity on the fringe modulation and the variation of the enhancement of the diffraction efficiency with fringe modulation at a fixed fringe velocity appropriate to high fringe modulations are experimentally investigated. It is shown that the diffraction at high fringe modulations, which corresponds to the high-spatial-frequency components of the Fourier spectrum, is enhanced by a factor of approximately 3.7, whereas the diffraction at low fringe modulations is suppressed by a factor of 0.6. The proposed technique has the advantages of real-time enhancement, arbitrary selection of the spatial frequency to be enhanced, and improved stability of the output. Experimental results of the edge enhancement of objects and edge-enhanced correlation are presented.

Compact optical correlator: pre-processing and filter encoding strategies applied to images with varying illumination

Abstract: We present a portable, versatile optical pattern recognition system that can process 256x256 pixel images at high speed. The system is fully controlled by Windows-based software and can easily be switched between VanderLugt and joint transform operation. It combines the advantages of optics and electronics to form an advanced hybrid system where pre- and postprocessing algorithms can be varied depending on the application. Simulation and experimental results show that edge enhancement combined with binarization gives good results when applied to images where the illumination is varying.

Real-time non-linear spatial filtering with a leaky OASLM

Abstract: In this paper we demonstrate image processing techniques such as edge enhancement and phase contrast by using an optically addressed liquid crystal spatial light modulator (OASLM) in the frequency plane of an optical 4f processor. The transfer function of the device is derived on the basis of the Jones formalism. Faced with a lack of a general theory for such non-linear optical processors, we show that an analogy to the propagation of optical pulses in fibres is helpful for the understanding of the image processing operation.

Sharpening edge features in digital image providing high frequency edge enhancement

Abstract: A method of sharpening edge features in a digital image having pixels which provide high spatial frequency edge enhancement including acquiring a digital image; computing an edge boost record having positive and negative boost values for different portions of the edge regions in a digital image; and modifying the edge boost values of edge related pixels in accordance with an edge boost modification function selected to provide an edge enhanced digital image.

Image edge detection and enhancement by an inversion operation.

Abstract: Edge extraction is an essential part of image processing. In digital image processing there are several optical methods for properly obtaining image edges. We propose a method of image edge extraction and enhancement by using a lens-based optical setup, the image, and its inverted form. The inverted and the noninverted images help here to obtain the image edges.

Edge enhancement using modified edge boost function

Abstract: A method of edge enhancing a digital image having pixels, includes acquiring a digital image; computing an edge boost function having positive and negative boost for different portions of the edge of the digital image; adjusting the edge boost function to produce a modified edge boost function such that the gain of the negative boost is greater than the gain of the positive boost; and applying the modified edge boost function to the digital image to provide an edge enhanced digital image.

Edge enhanced error diffusion with artifact correction in areas of highlights and shadows

Abstract: An error diffusion processor for preparing a document image for printing. Shadows and highlights regions stress error diffusion processes, because accumulated error cannot be easily compensated for in these regions. Edge enhancement emphasizes the problem by locally increasing error in order to maintain spatial detail of the image. The arrangement described puts an additional term into the error calculation that is a function of local intensity, with substantial value only in shadow and highlight regions to correct for edge enhancement artifacts.

Directional Unsharp Masking-Based Approach for Color Image Enhancement

Abstract: In this paper, we present an unsharp masking-based approach for noise smoothing and edge enhancing in multichannel images. The proposed structure is similar to the conventional unsharp masking structure, however, the enhancement is allowed only in the direction of maximal change and the enhancement parameter is computed as a nonlinear function of the rate of change. The proposed scheme enhances the true details, limits the overshoot near sharp edges and attenuates noise in flat areas. Moreover the use of the control function eliminates the need for the subjective coefficient λ used in the conventional unsharp masking technique.

The asterisk operator. An edge detection operator addressing the problem of clean edges in bone X-ray images

Abstract: Edge detection is a fundamental step in many machine vision or image processing applications and systems. The importance of edge detection increases as one seeks to increase the level of automation in the image processing system. The paper reports an edge detection operator which is fast in application to grey scale images and is sensitive to 'difficult' edges but not sensitive to artifacts such as scanner interlacing artifacts. The edge detection operator presented is simple but provides good detection of edges and clean and continuous edges across most of the image.

Edge-enhancement processing apparatus and method

Abstract: An edge-enhancement processing apparatus which removes problems of the conventional edge enhancement processing, which requires checking by an operator's visual observation or a high-frequency band filter, thus complicating the construction. A computer main body 21, as the nucleus of edge enhancement processing, calculates an edge amount as vector change level while generating a vector based on the difference values of data between adjacent pixels, at step S110, then selects and integrates edge amounts of only pixels having large edge amounts at steps S120 and S130, and obtains the mean value at step S230, to obtain the sharpness level of the image while adding attention to the pixels having large image change levels. The computer main body 21 determines an edge enhancement level Eenhance based on the image sharpness level. Thus, the computer main body 21 automatically performs edge enhancement processing at an optimum enhancement level.

Edge enhancement which reduces the visibility of false contours

Abstract: A method of edge enhancing a digital image having pixels which reduces the visibility of false edge contours and includes acquiring a digital image; computing an edge boost record having positive and negative boost values for different portions of the edge regions in a digital image; modifying the edge boost record by applying an adaptive blur kernel to the pixels of such edge boost record; and applying the modified edge boost record to the digital image to provide an edge enhanced digital image which reduces the visibility of false edge contours.

Image-processing method for noise suppression and sharpness emphasis for digital image

Abstract: PROBLEM TO BE SOLVED: To obtain an image with sharpness emphasized from an edge part and an image with good image quality, such as suppression of granularity from a granularity area by sharpening granularity noise included in an image, separating the edge part and flat parts of the image, detecting a granular signal from the flat part which is regarded as the granular area, dividing the granular part into small divisions and selectively eliminating them. SOLUTION: Weighted data WE, WG are used to separate edges and granular components from very small image data ΔIEG, mixed with edge and granular components and to generate a very small granular component, that is, a granularity suppression component G1 and an edge enhancement component E1 of an edge area. Then a multiple of a constant, e.g. a multiple of α is multiplied with the granularity suppression component G1 , and a multiple of a constant, e.g. a multiple of β is multiplied with the edge enhancement component E1 and the former product is subtracted and the latter product is added from/to a sharpness emphasis image IS having been obtained at first, so as to emphasize the sharpness of the edge of the image and a processed image I1 whose granularity of the flat part is suppressed is generated.

Unsharp masking-based approach for color image processing

Abstract: In this paper, we present an unsharp masking-based approach for noise smoothing and edge enhancing. And apply it to color image processing. The proposed structure is similar to the conventional unsharp masking structure, however, a nonlinear function is added to control the behavior of the operator. The proposed scheme enhances the true details, limits the overshoot near sharp edges and attenuates the noise in flat areas. Moreover the use of the control function eliminates the need for the subjective coefficient λ used in the conventional unsharp masking technique. Simulations show that the processed image presents sharp edges which makes it more pleasant to the human eye. Moreover, the amount of noise in the image is clearly reduced.

Processing, segmentation, and visualization of pre- and post-stent coronary arteries using intravascular ultrasound

Abstract: Intra-vascular ultrasound (IVUS) has significant potential for providing new information about the structure and condition of the coronary arteries. However, these image datasets are inherently noisy and characterized by frequent drop-outs and shadowing, considerably constraining their use for quantitative evaluation of coronary artery integrity and stent augmentation. A feasibility study was conducted to test the effectiveness of a software toolkit for processing, segmenting, and visualizing pre- and post-stent IVUS datasets, as a precursor to detailed quantitative evaluation of IVUS with regard to characterization of coronary luminal wall properties. Frame averaging, histogram processing, and anisotropic diffusion were used to reduce speckle noise and compensate for image dropout and shadowing. A region of interest (ROI) analysis was conducted to determine the effectiveness of the image processing. Preliminary results suggest that the image processing steps are effective at increasing the contrast to speckle ratio. In addition, contrast between the arterial wall and lumen was improved, producing an edge enhancement effect. Image registration was used to align images within a volume (i.e. 2-D registration) and between volumes (i.e. 3-D registration). A voxel matching method was used for the 2-D registration and a surface matching method was used for 3-D registration. A morphological connect method for segmentation was used to extract large structures in the data. A new edge-based algorithm was developed to segment the data in regions where the other method failed. Volume rendering methods were used to visualize the data. These preliminary visualizations of processed, segmented and registered IVUS datasets illustrated encouraging potential for further quantitative analysis of coronary artery morphology and pathology.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Binary phase-only 1/f joint transform correlator

Abstract: We present a new means of creating a binary phase only 1/f joint transform correlator using a ferroelectric liquid crystal spatial light modulator. By using the two-pass technique of the 1/f JTC in combination with a binary phase FLM SLM it is possible to build a mechanically robust correlator with a correlation rate in excess of 2 kHz. By using a checkerboard phase encoded input, it is possible to use the FLC SLM as a binary phase modulator while also avoiding the problem of CCD camera saturation due to zero order. An edge enhancement algorithm is then used on the captured image to produce a suitable image for the second pass through the correlator. The algorithm has been chosen to produce a near perfect binary phase image which results in a correlation plane with greatly suppressed zero order (or dc terms).