Showing papers on "Edge enhancement published in 2001"

Using the Canny edge detector for feature extraction and enhancement of remote sensing images

Abstract: Edges are important features in an image since they represent significant local intensity changes. They provide important clues to separate regions within an object or to identify changes in illumination. Most remote sensing applications, such as image registration, image segmentation, region separation, object description, and recognition, use edge detection as a preprocessing stage for feature extraction. Real images, such as remote sensing images, can be corrupted with point noise. The real problem is how to enhance noisy remote sensing images and simultaneously extract the edges. Using the implemented Canny edge detector for feature extraction and as an enhancement tool for remote sensing images, the result was robust with a very high enhancement level.

Adaptive threshold modulation for error diffusion halftoning

Abstract: Grayscale digital image halftoning quantizes each pixel to one bit. In error diffusion halftoning, the quantization error at each pixel is filtered and fed back to the input in order to diffuse the quantization error among the neighboring grayscale pixels. Error diffusion introduces nonlinear distortion (directional artifacts), linear distortion (sharpening), and additive noise. Threshold modulation, which alters the quantizer input, has been previously used to reduce either directional artifacts or linear distortion. This paper presents an adaptive threshold modulation framework to improve halftone quality by optimizing error diffusion parameters in the least squares sense. The framework models the quantizer implicitly, so a wide variety of quantizers may be used. Based on the framework, we derive adaptive algorithms to optimize 1) edge enhancement halftoning and 2) green noise halftoning. In edge enhancement halftoning, we minimize linear distortion by controlling the sharpening control parameter. We may also break up directional artifacts by replacing the thresholding quantizer with a deterministic bit flipping (DBF) quantizer. For green noise halftoning, we optimize the hysteresis coefficients.

Edge detection and sharpening process for an image

Abstract: A method and device for sharpening detected edges in an image to compensate for a corruption that occurs during the scanning and printing processes Edges are enhanced by increasing the contrast between two sides of an edge region according to the amount of distortion in the image signal at that location Each pixel in the image is analyzed in the context of neighboring pixels in the image to determine the presence of an edge and the degree of sharpening required A filter is applied to adjust the intensity value of pixels in an edge region to correct for distortion and to emphasize the edge The resulting final image contains sharpened edges with little effect on the smooth transition regions of the image

Image processing apparatus

Abstract: PROBLEM TO BE SOLVED: To provide an image processing apparatus and an image processing method which can perform optimum edge enhancement corresponding to the resolution of an output destination, and to provide a recording medium in which an image processing program is stored. SOLUTION: The image processing apparatus divides an image into rectangle units corresponding to the resolution of the output destination and obtains edge information from the respective divided rectangles. Then an edge enhancement processing is performed for each rectangle according to the edge information. Consequently, the optimum edge enhancement processing corresponding to the resolution of the output destination is carried out.

Text enhancement with asymmetric filter for video OCR

Abstract: Stripes are common sub-structures of text characters, and the scale of these stripes varies little within a word. This scale consistency thus provides us with a useful feature for text detection and segmentation. A new form of filter is derived from the Gabor filter, and it is shown that this filter can efficiently estimate the scales of these stripes. The contrast of text in video can then be increased by enhancing the edges of only those stripes found to correspond to a suitable scale. More specifically the algorithm presented here enhances the stripes in three pre-selected scale ranges. The resulting enhancement yields much better performance from the binarization process, which is the step required before character recognition.

Nonlinear diffusion in graphics hardware

Abstract: Multiscale methods have proved to be successful tools in image denoising, edge enhancement and shape recovery. They are based on the numerical solution of a nonlinear diffusion problem where a noisy or damaged image which has to be smoothed or restorated is considered as initial data. Here a novel approach is presented which will soon be capable to ensure real time performance of these methods. It is based on an implementation of a corresponding finite element scheme in texture hardware of modern graphics engines. The method regards vectors as textures and represents linear algebra operations as texture processing operations. Thus, the resulting performance can profit from the superior bandwidth and the build in parallelism of the graphics hardware. Here the concept of this approach is introduced and perspectives are outlined picking up the basic Perona Malik model on 2D images.

All-optical image processing by means of a photosensitive nonlinear liquid-crystal film: edge enhancement and image addition–subtraction

Abstract: We demonstrate two simple yet efficient all-optical image-processing techniques that use nonlinear photosensitive dye-doped nematic liquid-crystal films, namely, edge enhancement and image addition–subtraction operations. These films require no external bias and function at much lower optical powers and shorter response times than other conventional methods.

Adaptive edge detection and enhancement for image processing

Abstract: The present invention improves image quality by detecting and enhancing edges in an image Images often include blurry or fuzzy edges that can obscure an image An edge is a portion of an image separating two regions of substantially constant image intensity An image can be examined on a pixel-by-pixel basis to find a candidate edge When a candidate edge is found, a determination can made as to whether the candidate edge is a true edge A true edge can be enhanced by amplifying the image intensity differences between pixels on the true edge and adjacent pixels not on the true edge The present invention also provides a novel image processing filter for eliminating well-known noise from an image The image processing filter can further improve edge enhancement by eliminating such noise prior to the edge detection and enhancement

Image processing circuit and method for processing image

Abstract: The present invention relates to an image processing circuit and an image processing method, and is applied to, for example, a video camera, an electronic still camera and the like, for compressing the dynamic range at a high compression rate with evading the lowering of an impression concerning the contrast and the unnatural edge emphasis. The present invention smoothes an input image X while preserving the edge to obtain a gain correction coefficient, and corrects the pixel value x(i, j) of the input image X with the gain correction coefficient.

Device and method for processing image, recording medium and program

Abstract: PROBLEM TO BE SOLVED: To process an image while corresponding to the mixture of a background image and an image of a moving object. SOLUTION: An area specifying part 103 respectively specifies the pixels of an inputted image to be any among a foreground area, a background area and a mixed area, and supplies area information showing which each pixel belongs to among the foreground area, the background area and the mixed area to an area processing part 104. The area processing part 104 divides the inputted image in each of the foreground area, the background area or the mixed area on the basis of the area information supplied from the area specifying part 103 and performs image processing such as that generates a coefficient used in class sorting adaptation processing for generating an image of higher resolution in each divided inputted image, creates an image of higher resolution by applying the class sorting adaptation processing in each divided inputted image or applies edge enhancement processing with different degrees of edge enhancement by using respective different coefficients in each divided inputted image.

The AAPM/RSNA physics tutorial for residents: digital fluoroscopy.

Abstract: A digital fluoroscopy system is most commonly configured as a conventional fluoroscopy system (tube, table, image intensifier, video system) in which the analog video signal is converted to and stored as digital data. Other methods of acquiring the digital data (eg, digital or charge-coupled device video and flat-panel detectors) will become more prevalent in the future. Fundamental concepts related to digital imaging in general include binary numbers, pixels, and gray levels. Digital image data allow the convenient use of several image processing techniques including last image hold, gray-scale processing, temporal frame averaging, and edge enhancement. Real-time subtraction of digital fluoroscopic images after injection of contrast material has led to widespread use of digital subtraction angiography (DSA). Additional image processing techniques used with DSA include road mapping, image fade, mask pixel shift, frame summation, and vessel size measurement. Peripheral angiography performed with an automatic moving table allows imaging of the peripheral vasculature with a single contrast material injection.

Fuzzy anisotropic diffusion for speckle filtering

Abstract: An anisotropic diffusion filter controlled by fuzzy rules is presented. The proposed filter is based in the Perona-Malik technique, using fuzzy reasoning to calculate the diffusion coefficient which controls the whole diffusion. The method has the advantage that it can be used for both smoothing and noise cleaning, as well as edge enhancement. This new approach also allows us to model the diffusion process through a rule base to have a better performance. Some examples are given to illustrate the effectiveness of the proposed technique.

Tone-dependent error diffusion

Abstract: We present an enhanced error diffusion halftoning algorithm for which the filter weights and the quantizer thresholds vary depending on input pixel value. The weights and thresholds are optimized based on a human visual system model. Based on an analysis of the edge behavior, a tone dependent threshold is designed to reduce edge effects and start-up delay. We also propose an error diffusion system with parallel scan that uses variable weight locations to reduce worms.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A new method of acousto-optic image processing and edge enhancement

Abstract: The paper presents detailed results of research devoted to the development of a new acousto-optic method of spatial frequencies filtration The filtration of coherent optical beams is examined theoretically and basic statements of the investigation are confirmed experimentally A selection of partial rays forming optical images and control of their propagation directions are provided by the application of acousto-optic cells based on paratellurite single crystals Efficient regulation of the beams was executed in two orthogonal directions by means of the wide-angular regime of Bragg diffraction in the birefringent materials The advantages of this new method of image processing have been demonstrated during edge enhancement performed electronically in real time

Edge-enhancing super-resolution using anisotropic diffusion

Abstract: This paper presents an edge-enhancing super-resolution algorithm using anisotropic diffusion technique Because we solve the super-resolution problem by incorporating anisotropic diffusion, our technique does more than merely reconstruct a high-resolution image from several overlapping noisy low-resolution images and preserve them In addition to reducing image noise during the restoration process, our method also enhances edges We apply this technique to a video stream which can be aligned by 3/spl times/3 projective transformations

Self-similar intermediate asymptotics for nonlinear degenerate parabolic free-boundary problems that occur in image processing.

Abstract: In the boundary layers around the edges of images, basic nonlinear parabolic equations for image intensity used in image processing assume a special degenerate asymptotic form. An asymptotic self-similar solution to this degenerate equation is obtained in an explicit form. The solution reveals a substantially nonlinear effect—the formation of sharp steps at the edges of the images, leading to edge enhancement. Positions of the steps and the time shift parameter cannot be determined by direct construction of a self-similar solution; they depend on the initial condition of the pre-self-similar solution. The free-boundary problem is formulated describing the image intensity evolution in the boundary layer.

Image Processing for Numerical Approximations of Conservation Laws: Nonlinear Anisotropic Artificial Dissipation

Abstract: We employ a nonlinear anisotropic diffusion operator like the ones used as a means of filtering and edge enhancement in image processing and in numerical methods for conservation laws. It turns out that algorithms currently used in image processing are very well suited for the design of nonlinear higher order dissipative terms. In particular, we stabilize the well-known Lax--Wendroff formula by means of a nonlinear diffusion term.

Image decoding apparatus

Abstract: PROBLEM TO BE SOLVED: To solve the problems where, in a conventional MPEG image decoding apparatus, a low-pass filter may act even on the part which requires no noise removal because filtering is controlled based on a motion information for high quantization precision, and the block distortion is promoted by quantization error to degrade image quality if an edge enhancement filter is used. SOLUTION: While predicting appearance of block distortion and mosquitos with the use of the quantization information at encoding, a low-pass filter or an edge enhancement filter is appropriately selected to act on a decoded image, to raise quality of an output image. COPYRIGHT: (C)2003,JPO

Signal processing apparatus and method and image sensing apparatus

Abstract: In a signal processing apparatus for processing an image signal, a hue difference between adjoining pixels is detected by a color image edge detector, and an aperture control main gain circuit amplifies a luminance signal using a gain determined on the basis of the hue difference detected by the color image edge detector to enhance an edge pixel of an image.

Observer-dependent image enhancement

Abstract: In many image-processing applications the image quality should be improved to support the human perception. Image quality evaluation by human observers is, however, heavily subjective in nature. Individual observers judge the image quality differently. In many cases, the quality of the relevant part of image information, which is perceived by the observer, should reach a maximum. In previous works, an overall system for subjective image enhancement, which is based on fusion of different algorithms, was introduced. In this paper, more details of the overall-system structure are provided. Furthermore, the test results for contrast and sharpness/smoothness as interesting image qualities are also presented.

Intensity filtering of a two-dimensional optical image in high-performance photorefractive mesogenic composites

Abstract: Edge enhancement, a type of intensity filtering of a two-dimensional optical image, was demonstrated using a high-performance photorefractive polymer-dissolved liquid crystal. We calculated the expected images using Fourier transform holographic geometry and obtained good agreement between the observed images and the theoretical expectation.

Improved algorithm for computerized detection and quantification of pulmonary emphysema at high-resolution computed tomography (HRCT)

Abstract: Emphysema is characterized by destruction of lung tissue with development of small or large holes within the lung. These areas will have Hounsfield values (HU) approaching -1000. It is possible to detect and quantificate such areas using simple density mask technique. The edge enhancement reconstruction algorithm, gravity and motion of the heart and vessels during scanning causes artefacts, however. The purpose of our work was to construct an algorithm that detects such image artefacts and corrects them. The first step is to apply inverse filtering to the image removing much of the effect of the edge enhancement reconstruction algorithm. The next step implies computation of the antero-posterior density gradient caused by gravity and correction for that. Motion artefacts are in a third step corrected for by use of normalized averaging, thresholding and region growing. Twenty healthy volunteers were investigated, 10 with slight emphysema and 10 without. Using simple density mask technique it was not possible to separate persons with disease from those without. Our algorithm improved separation of the two groups considerably. Our algorithm needs further refinement, but may form a basis for further development of methods for computerized diagnosis and quantification of emphysema by HRCT.

Clipping circuit and image processing device employing such a clipping circuit

Abstract: In an image processing device, an edge detecting circuit 1 produces edge signals that represent edge components present in image signals, and an adder circuit 2 superimposes the edge signals on the image signals to produce edge-enhanced image signals. The image signals before edge enhancement are fed to a range setting circuit 3 so that, based on the image signals preceding and following a target image signal that is about to be processed by a clipper 4, a range in which the data value of the target image signal is allowed to vary is set. Based on the range of data values thus set by the range setting circuit 3, the clipper 4 clips the data values of the edge-enhanced image data.

Tactile differentiator

Abstract: This paper proposes the tactile differentiator that can enhance the edge of polygonal surface, through tracing motion. It is composed of a flexible beam anchored at the base with a moment sensor, and an actuator for moving the whole system. When the beam tip passes over the edge where two different planes are intersected with an arbitrary angle, the tactile differentiator provides a step change of output, as if it were just like a differentiator. The edge enhancement factor of sensor is introduced by the shape of beam, the intersection angle of environment, and the contact friction. By using the factor, we discuss the design of the sensor. Experimental results are also shown to verify the basic idea.

Image processor and method for processing image

Abstract: PROBLEM TO BE SOLVED: To obtain an image processor capable of accurately performing recognition processing even of an image in which a luminance distribution situation is not adequate to recognition processing because of a small number of textures. SOLUTION: This image processor is provided with a texture increasing means for performing texture increasing processing (step S111) that increases textures with edge enhancement, etc., with respect to an image being as a recognition processing object and a texture background differentiating means for performing background differentiation processing (step S102) that pays attention to textures.