Showing papers on "Edge enhancement published in 1997"

Sidescatter x-ray detection system

Abstract: An edge enhancement X-ray imaging system inspects an object (10) for detecting an illegal component. The system illuminates the object (10) with penetrating radiation (11) which is sidescattered from the object (10) and captured by a pair of radiant detectors (14, 16). The detectors (14, 16) are symmetrically positioned opposite each other, being adjacent the two sides of the object (10). Each detector has a detecting surface substantially parallel to the beam for converting sidescattered radiation into a pair of electrical signals which define a location of an edge of the illegal component. In response to the electrical signals, a video display (20) produces a visual image of the edge. In another embodiment of the invention, the system further comprises a pair of backscatter detectors which convert the backscattered radiation into a second pair of electrical signals producing a second visual image on the video display (20). As a result of superimposing the second image onto the first image associated with the sidescatter detectors, the detection of components of the object is greatly improved.

An integrated cortical layer for orientation enhancement

Abstract: This paper presents a set of two analog chips performing the following chain of operations: phototransduction of an image projected on the first chip, edge enhancement by high-pass filtering, current-to-pulse frequency conversion of the filtered image, and pulse coded transmission of the filtered image to the second chip which generates a "projective field" whose shape and size are widely programmable through few bias lines. The end result of the processing chain is an image with enhanced edges along a programmable orientation. The design of this system draws from the knowledge gathered by neurobiologists about the first steps of visual perception: retinal image processing and coding followed by "simple cells" processing in the visual cortex. The focus of the paper is on the cortical layer chip since information about the retina is available elsewhere. The system's main advantages are real time operation and ease of module interconnection for true parallel processing.

A generic 2D sharpness enhancement algorithm for luminance signals

Abstract: In this paper we attempt to generalize a sharpness enhancement technique for TV applications. Basically, the enhancement is accomplished by adding overshoot to luminance edges. However, the optimal amount of overshoot added for a high image quality depends on the local image statistics. For this purpose, four properties of the video signal are analysed locally by separate units and depending on this analysis, we regulate the amount of sharpness enhancement to be provided. Due to these additional controls, the system is robust with respect to varying image statistics and yields a high performance.

Nonlinear operators in image restoration

Abstract: We present a variational approach such that during image restoration, edges detected in the original image are being preserved. We compare the mathematical foundation of this method with respect to some of the well known methods recently proposed in the literature within the class of PDE based algorithms (anisotropic diffusion, mean curvature motion, min/max flow technique). The performance of our approach is carefully examined and compared to the classical methods. Experimental results on synthetic and real images illustrate the capabilities of all the studied approaches.

Image pickup apparatus with interpolation and edge enhancement of pickup signal varying with zoom magnification

Abstract: The amount of edge enhancement outputted from an amount-of-edge-enhancement computing circuit is determined on the basis of the degree of sharpness of the edge independently of a zoom magnification. In the meantime, in an enhancement coefficient computing circuit, an enhancement coefficient according to the zoom magnification is computed. In a multiplier, the output from the amount-of-edge-enhancement computing circuit (the amount of edge enhancement) is multiplied by the output from the enhancement coefficient computing circuit (the enhancement coefficient). The resultant amount of edge correction is outputted from the multiplier. Accordingly, the amount of edge correction outputted from the multiplier takes a value according to the zoom magnification. According to this arrangement, enhancement processing which does not bring about overcorrection or unprocessing can be applied to the edge portion of an image enlarged by electronic zoom. In consequence, it is possible to enhance the apparent resolution of the image enlarged by electronic zoom.

Noise reduction apparatus for electronic edge enhancement

Abstract: A video signal processor includes an edge enhancement determining circuit that senses the amount of some characteristic of that signal which provides a measure of noise inherent in the signal, precisely determines a preferred amount of edge enhancement to be applied to a video signal as a function of that characteristic, and applies that amount of edge enhancement to the video signal. The video signal characteristic, used to determine the noise content of the video signal includes the amount of automatic gain control amplification and the brightness of the viewed scene. Thus, the amount of edge enhancement added to the video signal is adaptively controlled according to the brightness level of the viewed scene and the amplification level of the video signal by the automatic gain control circuit, and provides the proper amount of edge sharpness to the viewed video scene as a function of its noise content. This provides an increase in perceived sharpness of the viewed image, without an increase in background noise that occurs in conventional non-adaptive systems.

Basic image-processing operations by use of acousto-optics

Abstract: We describe some basic optical image-processing operations with acousto-optic (AO) Bragg diffraction. Instead of using frequency-plane filters, we place an AO cell behind the object. We then realize experimentally one-dimensional edge enhancement, which utilizes a high-pass filtering effect in the undiffracted order from the AO cell. A numerical simulation compares well with the experimental results. With two AO cells oriented orthogonally to each other, a second-order mixed derivative operation, evident from the four-corner enhancement of a square, is also demonstrated.

Algorithms for color image edge enhancement using potential functions

Abstract: This letter deals with the color image edge enhancement issue using clustering ideas and based on the use of potential functions (Parzen windows). Two algorithms are proposed. The first uses potential functions (PF's) and selects the output as the vector maximizing the PF. The second one elaborates further by employing the mountain clustering method and modifying it appropriately. Both algorithms are robust in the presence of noise, Gaussian and impulsive.

Real-time edge enhancement of femtosecond time-domain images by use of photorefractive quantum wells

Abstract: Dynamic holograms written in a photorefractive multiple quantum well placed inside a Fourier femtosecond pulse shaper convert a space-domain image into the time domain. We demonstrate that edge-enhancement processing of the time-domain image can be performed by controlling hologram-writing intensities.

Properties of minimum cross-entropy reconstruction of emission tomography with a morphologically based prior

Abstract: The authors have studied the properties of a minimum cross-entropy (MXE) algorithm for emission tomography reconstruction with anatomical prior images. MXE is implemented with two terms: a maximum likelihood expectation maximization term and a penalty term for regularization within anatomically defined boundaries. The relative emphasis put on the two competing terms is controlled by the regularization constant /spl beta/. Edge resolution and noise level were compared for reconstructions with and without corresponding prior image. The prior lends to significant edge enhancement with edge resolution converging to a lower limit independent of /spl beta/. Normalized standard deviation (NSD) and resolution both illustrate that regularization within boundaries behaves predictably with more smoothing for larger /spl beta/. Application of ordered subsets (OS) was also investigated. For OS, edge enhancement is fully preserved but NSD increases for low subset size. Results demonstrate that OS is applicable to MXE provided subset size is greater than 4. OS-MXE has appealing properties for regularized reconstruction.

Self-adaptive spatial filtering by use of azo chromophores doped in low glass-transition-temperature polymers.

Abstract: We report on self-adaptive spatial filtering by combination of the self-adaptive polarization-rotation property of Disperse Red 1–doped polymers with low glass-transition-temperature and Fourier-transform operation. Our system can be operated with only an action beam with object information and without a probe beam for image readout. Edge enhancement by the action beam–probe beam is demonstrated as an example of the system’s application to spatial filtering.

Near-field optical microscope image formation: a theoretical and experimental study.

Abstract: A quantitative comparison between theory and experiment has been carried out for a collection-mode near-field optical microscope. A 30-nm (lateral dimension) cylindrical dielectric sample was imaged. This image was compared with the result of theoretical calculations that used a classical macroscopic nonglobal model based on the excitation theorem. Good agreement was obtained, with image inversion, edge enhancement, and edge asymmetry correctly predicted.

Image processing method and apparatus employing the same

Abstract: An image processing apparatus obtains image data with a low resolution by processing a plurality of pixel values read in with a high resolution into one pixel value, for the low resolution mode. Thereby, the image processing apparatus is able to transmit unfailingly image data needed for reproduction of a narrow line in a document even during a low-resolution mode. Further, in accordance with a resolution mode that is currently selected, an image processing apparatus adjusts the ratio between the amount of edge enhancement with respect to the main scanning direction and the amount of edge enhancement with respect to the sub-scanning direction, thus unfailingly including the image data needed for reproduction of a narrow line extending in the main and/or sub-scanning direction.

Enhancement of image edge sharpness and acutance

Abstract: We have recently proposed an objective measure of edge sharpness or acutance of a region of interest (ROI) in the image. As acutance is related to image sharpness, one possible approach to image enhancement is to apply enhancement techniques in such a way as to increase the acutance of the ROI. Then, we may expect the perceived sharpness of the ROI to be increased as a result. A new image sharpening method designed on the basis of acutance is proposed in this paper. In this method, 1D operators are applied to sets of pixels along the normals at each boundary pixel of an ROI. It is shown that the method can improve sharpness without creating significant artifacts.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Optimized image processing algorithms for a single sensor camera

Abstract: Optimizing the necessary image processing algorithms for a color single sensor camera is investigated. The color interpolation, edge enhancement, and color correction algorithms and the optimizing effects are presented.

Image edge enhancement, dynamic compression and noise suppression using analog circuit processing

Abstract: We designed circuits that have potential use as preprocessors of noisy image data, which vary in intensity over as much as four orders of magnitude. The circuits are based on equations representing a stage of the Boundary Contour System/Feature Contour System model. We compared the model performance (equations) using Gaussian and exponential filters with the simulated circuit performance. Our circuits achieved compression of up to four orders of input range, while maintaining contrast ratios in local regions. Edge enhancement is maintained down to a SNR of -20 dB, and at that noise level the circuit's RMS error performance is comparable to that of the mathematical formulation. For quantitative display purposes, we present responses to test stimulation a linear array of circuits. A 15/spl times/15 array design is also presented.

Image enhancement using color and spatial information

Abstract: In this paper, a new filter that performs color image enhancement is presented. The filter achieves this through the minimization of a weighted cost function. The weights are determined using potential functions which are calculated in such a way as to convey spatial information. Application of the proposed filter on a real blurred and noisy color image is performed to verify its enhancement capabilities.

A New Bio-inspired Algorithm for Early Vision Edge Detection and Image Segmentation

Abstract: We present a new bio-inspired algorithm for early vision image preprocessing that includes both edge detection and image segmentation. Previous research efforts either implemented Difference-of-two-Gaussians (DoG) bandpass filtering with resistive networks for edge detection or image segmentation with so-called resistive fuses. By using a feedback mechanism, we combine the superior edge detection algorithm of two-layer parallel resistive networks with image segmentation. To allow an early estimation of the results achievable with this algorithm, a special simulation program was developed which simulates the behavior of an idealized electric circuit implementation of this algorithm. Simulation results not only for the new proposed algorithm but also for two-layer resistive networks and for networks with resistive fuses are presented. Moreover, the development of the simulation program also led to a new effective method for subsequent implementation of the algorithm.

Scale space contours and localization property of a Gaussian derivative edge enhancement operator

Abstract: One of the nice properties of the Gaussian scale space map is its well behavedness. This rather well behaved nature is somewhat deceptive, however, as portions of the map may not have any direct relationship to the features in the unfiltered image. It has been shown that not all zero-crossing surface patches can be associated with intensity changes in the unfiltered image. Zero-crossings give rise to both authentic and phantom scale map contours. Recently, we proposed an edge enhancement operator, the LWF, which is a weighted combination of the Gaussian and its second derivative. In this paper, we provide mathematical proof that the LWF produces only the authentic scale map contours. We also show that the LWF has an excellent localization property (that is the points marked by the operator is very close to center of the true edge). Performance comparison between the Laplacian of Gaussian and LWF operators with respect to the localization property is also presented with a number of computer simulations.

Real-time robust line detection in microscopy images

Abstract: We discuss an algorithm to detect lines in low contrast images in the presence of noise. The image we consider are orientation imaging microscopy (OIM) images of metal surfaces. The objective is to locate lines (boundaries between grains) in the OIM images and use that information to determine where three grains intersect (triple junctions). We use a novel method for fusion edge enhancement and a new fast skeletonization procedure using a new and efficient hit and miss transform (HMT) that produces lines of one pixel width.

Color image enhancement using local density function estimators

Abstract: In this work two combinations of potential and Euclidean-based functions that lead to edge enhancement of color images are proposed. Potential functions are calculated at each pixel's neighbourhood, embodying spatial information and are used as local density estimators for the image. Color similarity information is included in the Euclidean distances in the RGB color space.

Aliasing artifact suppression with adaptive segmentation based edge enhancement

Abstract: One of the inherent limitations of the third generation CT scanner is the projection undersampling. Because of the fan-beam geometry, patient motion, and many other factors, the Nyquist sampling criteria are not always strictly observed. As a result, the fine structures of the anatomy and important pathologies are often marred by aliasing streaks, which render the image unusable. We analyze the root cause of the aliasing artifact and present an adaptive algorithm that enhances the fine structures of the anatomy and suppresses aliasing artifacts and noise. The algorithm first reconstruct an image with a modified reconstruction kernel which preserves as much high frequency information as possible without introducing significant aliasing artifacts. The resulting image is then segmented into two classes. A fuzzy classification method is employed which uses not only the pixel intensity and texture information, but also the classifications of adjacent slices. Various phantom and clinical studies have demonstrated the robustness and effectiveness of our approach.

Estimation of the Color Image Gradient with Perceptual Attributes

Abstract: Classical gradient operators are generally defined for grey level images and are very useful for image processing such as edge detection, image segmentation, data compression and object extraction. Some attempts have been made to extend these techniques to multi-component images. However, most of these solutions do not provide an optimal edge enhancement.

Fast Turnaround of a Structured Custom IC Design Using Advanced Design Tools and Methodology

Abstract: The HP IMACC chip was developed to provide image processing capabilities. The initial target application is medical imaging with geological applications as a potential area of expansion. The graphical capabilities of IMACC include spatial filtering, edge detection and enhancement, image pan and zoom, image rotation, and window and level control. IMACC consists of three major components: The convolver circuit has a 33 programmable kernel* and can perform low-pass or high-pass spatial filtering, edge enhancement, and other functions. The interpolator is an implementation of a 44 bicubic convolution kernel.* The interpolator can be configured to perform pan, zoom, and rotation. A RAM-based lookup table is used for windowing and leveling of image pixel intensities. In support of the various user-selectable operating modes, any or all three of the functional blocks may be active at a time. The order of operations can be changed as desired, with the single limitation that the convolver must precede the interpolator if both modules are in the chain. When the image visualization accelerator board (IMACC is the heart of this board) is attached to the HP HCRX graphics subsystem, simultaneous convolution, zoom, rotation, and window and level control of 1024-by-1024 pixel, 16-bit medical images at 40 frames per second are possible. The accelerator can process more than 40 million pixels per second independent of the number or order of internal operations.

Image Gathering and Restoration

Abstract: This chapter focuses the mathematical development begun in Chapter 2 on digital image restoration. First, Section 3.1 develops the unconstrained Wiener filter that restores the image with an interpolation lattice that is sufficiently dense to completely suppress the blurring and raster effects of the image-display process. Therefore, the resultant image has the absolute minimum mean-square restoration error (MSRE) for any given image gathering and display devices. Next, Section 3.2 extends the development to the constrained Wiener filter that allows the density of the interpolation to be constrained and, therefore, must account for the blurring and raster effects of the image-display process. Section 3.3 further extends the development to the Wiener-characteristic filter that includes a linear filter to minimize the MSRE for a particular spatial feature of the scene, such as edges and boundaries. Section 3.4, in turn, develops the small-kernel Wiener filter that allows the amount of digital processing to be constrained as well as the density of the interpolation. Finally, Section 3.5 presents the Wiener-Gaussian enhancement (WIGE) filter that combines the Wiener filter with an enhancement function that allows the user to interactively control the visual quality of the restored image.

Noncausal error-diffusion method for edge enhancement

Abstract: Various modifications to the Floyd-Steinberg's error diffusion algorithm have been proposed to reduce the undesirable artifacts or to enhance the edges on the error diffused image. Most of the existing error diffusion techniques utilize the error diffusion kernel defmed on the causal image plane with respect to the raster scanning directions. In this paper, an error diffusion kernel containing non-causal neighbors is proposed for edge enhancement. The error diffusion kernel for individual gray level is first estimated by minimizing the error criterion defined for the input gray level ramp image and its output binary image. The proposed error diffusion kernel is then calculated by taking an average of the estimated error diffusion kernels representing mid-tone gray levels. Experiments are performed to examine the proposed error diffusion method. Experimental results indicate that the binary images obtained by the proposed error diffusion kernel exhibit the enhanced edges compared to those from the existing error diffusion techniques.

Performance enhancement in acousto-optic image processing

Abstract: From the transfer functions of an acousto-optic (AO) cell, it is found that some basic image processing can be accomplished by using AO cells. Instead of frequency-plane filters, the AO cells are placed directly behind the object. The one dimensional edge enhancement results using one AO cell can be improved by using two acousto-optic cells which are put in tandem and with contra-propagating sound. The dominant second derivative operation obtained from the transfer function of the undiffracted order works like a one-dimensional Laplacian operator which enables improved edge enhancement.

Simulated retinal center/surround artificial neuroprocessing using analog VLSI

Abstract: We designed an array of CMOS circuits to realize part of a model of a biological retina that acts as a preprocessing stage in a Boundary Contour System/Feature Contour System1. The basis for the circuitry is a shunting neuron equation. The “membrane” voltage of this silicon neuron hyperpolarizes as a function of the surround excitation and depolarizes as a function of the center excitation. The electronics approximates a Difference of Gaussians operator for edge enhancement. That quantity is scaled by an approximation to a Sum of Gaussians operator. Thus, the output reports on contrast that is normalized by the image’s absolute intensity in a local region.