Showing papers on "Edge enhancement published in 2007"

Data processing and image reconstruction methods for pixel detectors

Abstract: Semiconductor single-particle-counting pixel detectors offer many advantages for radiation imaging: high detection efficiency, energy discrimination, noiseless digital integration (counting), high frame rate and virtually unlimited dynamic range. All these properties allow to achieve high quality images. Examples of transmission images and 3D tomographic reconstruction using X-rays and slow neutrons are presented demonstrating effects that can affect the quality of images. A number of obstacles can limit detector performance if not handled. The pixel detector is in fact an array of individual detectors (pixels), each of them has its own efficiency, energy calibration and also noise. The common effort is to make all these parameters uniform for all pixels. However, an ideal uniformity can be never reached. Moreover, it is often seen that the signal in one pixel affects neighboring pixels due to various reasons (charge sharing, crosstalk, etc.). All such effects have to be taken into account during data processing to avoid false data interpretation. The main intention of this contribution is to summarize techniques of data processing and image correction to eliminate residual drawbacks of pixel detectors. It is shown how to extend these methods to handle further physical effects such as hardening of the beam and edge enhancement by deflection. Besides, more advanced methods of data processing such as tomographic 3D reconstruction are discussed. All methods are demonstrated on real experiments from biology and material science performed mostly with the Medipix2 pixel device. A brief view to the future of pixel detectors and their applications also including spectroscopy and particle tracking is given too.

Mathematical-morphology-based edge detectors for detection of thin edges in low-contrast regions

Abstract: A new edge detector based on mathematical morphology to preserve thin edge features in low-contrast regions as well as other apparent edges is proposed. A quad-decomposition edge enhancement process, a thresholding process, and a mask-based noise filtering process were developed and used to enhance thin edge features, extract edge points and filter out some meaningless noise points, respectively. Moreover, five bipolar oriented edge masks were also designed to remove most of the incorrectly detected edge features. Many experiments were conducted to evaluate and compare the performance of the proposed algorithm and several conventional ones. Pratt's figure of merit achieved by the proposed algorithm was as high as 92.5. The comprehensive experimental results show that the proposed algorithm is capable of preserving thin edge details successfully in low-contrast regions and is robust against noise.

System and method for detecting edges in a video signal

Abstract: A system and method for processing a digital video signal corresponding to an image are provided. A plurality of independent edge detecting processes or edge detector modules detect a set of edges and at least one additional edge that is not included in the set of edges. An edge map includes data regarding all edges identified by any edge detecting process or module, and a visually perceptible artifact of the image is altered based at least in part on an evaluation of the edge map. The system and method detects and filters block artifacts and ringing or other noise from digital images, resulting in reduced image distortion.

Local Variance-Controlled Forward-and-Backward Diffusion for Image Enhancement and Noise Reduction

Abstract: In order to improve signal-to-noise ratio (SNR) and contrast-to-noise ratio, this paper introduces a local variance-controlled forward-and-backward (LVCFAB) diffusion algorithm for edge enhancement and noise reduction. In our algorithm, an alternative FAB diffusion algorithm is proposed. The results for the alternative FAB algorithm show better algorithm behavior than other existing diffusion FAB approaches. Furthermore, two distinct discontinuity measures and the alternative FAB diffusion are incorporated into a LVCFAB diffusion algorithm, where the joint use of the two measures leads to a complementary effect for preserving edge features in digital images. This LVC mechanism adaptively modifies the degree of diffusion at any image location and is dependent on both local gradient and inhomogeneity. Qualitative experiments, based on general digital images and magnetic resonance images, show significant improvements when the LVCFAB diffusion algorithm is used versus the existing anisotropic diffusion and the previous FAB diffusion algorithms for enhancing edge features and improving image contrast. Quantitative analyses, based on peak SNR, confirm the superiority of the proposed LVCFAB diffusion algorithm.

Apparatus for and method of processing digital image

Abstract: An apparatus for and method of processing a digital image are provided. The apparatus for processing a digital image includes: a detection unit which detects the direction or a magnitude of an edge of an input image signal; and an edge enhancement unit which determines the degree of enhancing the edge based on the detected direction or the detected magnitude of the edge, and enhances the edge of the input image signal according to the determined degree of enhancement.

Image processing apparatus

Abstract: An image processing apparatus includes: an image pickup section for converting an object light into image signals of Bayer RGB array; a color information detecting section for obtaining color information of the object from the image signals obtained by the image pickup section; a first luminance data generating section for finding luminance data for use in edge enhancement processing based on G signals of the image signals obtained by the image pickup section; a second luminance data generating section for finding luminance data for use in edge enhancement processing based on all color signals of the image signals; a selector for providing an output by switching between outputs of the first and second luminance data generating section; and a selection signal generating section for generating selection signal for controlling the switching of the selector based on color information obtained at the color information detecting section The image processing apparatus is thereby achieved as capable of edge enhancement processing at favorable S/N and with less occurrence of edge noise in high saturation regions and low saturation regions

Spiral Phase Microscopy

Abstract: Publisher Summary This chapter discusses the spiral phase contrast method that has interesting applications in optical microscopy and interferometry. In microscopy, a spiral phase contrast filter with an absorptive central point (blocking the zero-order Fourier component of the image wave) can be used for an isotropic edge enhancement of both amplitude and phase samples. This type of isotropic edge contrast has advantages in applications such as cell counting with respect to typically used one-dimensionally oriented contrasting methods, such as differential interference contrast (DIC microscopy). Conversely, a spiral phase filters with a transmissive center produces a relief-like shadow image of a sample. Another important feature of the relief-like shadow images is that their apparent shadow direction can be easily rotated by shifting the phase of the central point of the spiral phase filter or by simply rotating an on-axis spiral phase filter.

Phase contrast enhanced high resolution X-ray imaging and tomography of soft tissue

Abstract: A tabletop system for digital high resolution and high sensitivity X-ray micro-radiography has been developed for small-animal and soft-tissue imaging. The system is based on a micro-focus X-ray tube and the semiconductor hybrid position sensitive Medipix2 pixel detector. Transmission radiography imaging, conventionally based only on absorption, is enhanced by exploiting phase-shift effects induced in the X-ray beam traversing the sample. Phase contrast imaging is realized by object edge enhancement. DAQ is done by a novel fully integrated USB-based readout with online image generation. Improved signal reconstruction techniques make use of advanced statistical data analysis, enhanced beam hardening correction and direct thickness calibration of individual pixels. 2D and 3D micro-tomography images of several biological samples demonstrate the applicability of the system for biological and medical purposes including in-vivo and time dependent physiological studies in the life sciences.

A New Model-Based Digital Halftoning and Data Hiding Designed With LMS Optimization

Abstract: This work employs the well known least-mean-square (LMS) method to design an adaptive filter to produce high-quality halftone images. The filter can be regarded as a transformation medium between original gray level images and corresponding halftone images. Experimental results indicate that the proposed LMS-designed halftoning offers the extra benefit of edge enhancement. Since a halftone image is typically used in printing, a modified printer model, which can coordinate with the proposed LMS-designed halftoning, is proposed to eliminate the harm caused by the dot-gain effect in printing. Moreover, two data hiding applications, the direct embedding LMS-designed halftone technique (DELDH) and the information sharing LMS-designed halftone technique (ISLDH), are proposed to demonstrate the performance of the proposed LMS-designed halftoning. The experimental results show that, both techniques can be used with the proposed modified printer model to achieve excellent image quality and decoded visual patterns

Picture reinforcing treatment system and treatment method

Abstract: The system includes following parts: image buffer; image analyzer in multiple scales connected to the image buffer; fuzzy logic controller (FLC) connected to the image analyzer in multiple scales; edge enhancement processor connected to image buffer and FLC; noise remover connected to connected to image buffer and FLC; synthesizer connected to image buffer, noise remover, edge enhancement processor, and FLC. The method includes following steps: based on fetched original image data to obtain edge information of original image; based on edge information of original image to obtain variance of gain and noise of original image; based on calculated data of edge enhanced image and noise removed image to obtain final processed data. Using edge analysis in multiple scales, under control of fuzzy logic, the invention realizes self-adaptive noise reduction process and edge enhancement process for images.

Image Pre-processing Algorithm Based on Lateral Inhibition

Abstract: Enhancing the contrast and projecting the edge is the two important functions of the lateral inhibition network. Some image details are lost when the infrared image is processed based on traditional lateral inhibition algorithm. A new method that the processed image is weightingly added to the original one is proposed. The algorithm can not only project the image edge, but also overcome the above-mentioned shortage. The simulation results show its effectivity.

Ultrasonic Image Processor

Abstract: Non-linear processing is performed in which noise reduction (smoothing) is serially performed for original data to reduce high-frequency noise components, the edge enhancement processing is performed for the smoothed image and, after that, noise components are reduced again. Finally, the created image is weighted-combined with the original image.

Image processing of an incoming light field using a spatial light modulator

Abstract: A method, computer-usable medium and a system for varying an incoming light field are disclosed. Embodiments provide mechanisms for performing image processing on an incoming light field using a spatial light modulator which is adjusted based upon characteristics of the incoming light field. The spatial light modulator may be positioned between the viewed scene and the eye, and therefore, may be semi-transparent. The image processing may consist of tone mapping, color enhancement, beautification, edge enhancement, spectral separation of colors, spectral separation of metamers, object emphasis, other image processing, or some combination thereof. Additionally, embodiments compensate for parallax errors by adjusting the spatial light modulator based upon the position of an observer with respect to the spatial light modulator. And further, embodiments may be incorporated into optical devices, wearable optical devices, windows, windshields, and the like, where the semi-transparent spatial light modulator adjusts the image before entering the eye.

Feature Preserving Nonlinear 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.

X ray picture edge and contrast synthesis enhancing method

Abstract: The invention relates to the field of image processing technology, in particular to an image enhancement processing method for an industrial or medical X-ray image inspection system. The method comprises the following steps of : S1. inputting a collected X-ray image; S2. enhancing image edges by adopting Laplacian edge enhancement algorithm which can adjust intensity; S3. processing each detail in the enhanced image by adopting quick local histogram equalization (LHE) ; S4. stretching the gray range of the image data which has been processed through the step S3; S5. outputting the enhanced image. Compared with the perspective image enhancement algorithm on prior inspection equipment, the invention has the advantages of better enhancement result, adaptive ability, high automation degree, simple operation and quick execution.

Curvature-based stroke rendering

Abstract: This paper describes an algorithm that renders lines that have various thicknesses and have sharp tapered ends. This algorithm does not require any special information on each local point of a line. The thickness is determined by curvature and lengths from both ends. Therefore the algorithm is applicable in a variety of line rendering situations, such as 3D rendering engines for high quality cel-animation-like effects, reuse of geometrical data designed by CAD for advertising purposes, edge enhancement in a photo retouching process with edge detection methods and so on. In addition, using the generated varying thicknesses, we have developed algorithms for shading and embossing effects.

Fuzzy morphology for edge detection and segmentation

Abstract: This paper proposes a new approach for structure based separation of image objects using fuzzy morphology. With set operators in fuzzy context, we apply an adaptive alpha-cut morphological processing for edge detection, image enhancement and segmentation. 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 overlayed on the original for enhanced boundaries. Experiments were performed using real images of aerial views, sign boards and biological objects. A comparison to other edge enhancement techniques like unsharp masking, sobel and laplacian filtering shows improved performance by the proposed technique.

Image processing method and apparatus for contrast enhancement

Abstract: Provided are an image processing method and apparatus for enhancing contrast. The image processing apparatus includes a determination unit that determines whether contrast enhancement processing should be performed on an input image; an intensity mapping unit that generates a plurality of images having different exposure times from the input image, using intensity mapping, if the contrast enhancement processing should be performed on the input image; and an image composition unit that composes the plurality of images into a composed image. Therefore, it is possible to reduce a color change or a false contour phenomenon that are generated in a related art contrast enhancement process.

Edge adjustment method, image processing device and display apparatus

Abstract: A noise removing filter removes noise from an input image and an edge component extracting unit extracts edge components. The edge components are extracted by calculating a difference between the input image and a smoothed image, which is obtained by smoothing the input image in a smoothed image generating portion. An edge component comparing unit compares the extracted edge components with a threshold value and a sum calculating unit calculates the sum of the edge components greater than the threshold value. A control circuit determines, the enhancement degree of the edges based on the sum and averaged luminance of the input image calculated by an average luminance calculating unit. An enhancement degree adjustment unit adjusts the determined enhancement degree, and an edge component enhancement unit enhances the edge components based on this enhancement degree and adds it to the input image to perform edge enhancement processing.

An Effective Method to Colour Medical Image Enhancement

Abstract: Image enhancement technology plays a very important role In image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. Colour medical image is becoming more and more significant in medical diagnosis. In this paper, an enhancement arithmetic used for colour medical image is discussed. After the enhancement based on wavelet analysis, the color space transform method is applied to the color medical image. The method can improve the image sharpness and make the image characteristics more evident. The enhancement result is useful for further analysis.

Edge Enhancement and Filtering of Medical Ultrasonic Images Using a Hybrid Method

Abstract: A hybrid method based on anisotropic diffusion (AD) is proposed for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the different denoising properties of three techniques: median filtering, improved AD filtering and isotropic diffusion filtering. The gradient matrix is analyzed, and thresholds are chosen by experiments. The hybrid method is made by combining the three filtering methods for three different grayscale gradient ranges respectively. The filtering program is realized by iteration, with iteration time determined by iteration stopping criterion (ISC) accurately. In the experiment hundreds of images are processed by hybrid method, in contrast with median filtering and speckle reducing anisotropic diffusion (SRAD) filtering. The experimental results shows hybrid method can greatly improve processing speed, while successfully suppress speckle and enhance edge, therefore suitable for high-speed noise elimination of 3D images with huge data.

An Improved Algorithm for the Lane Recognition of Structured Road

Abstract: Based on a high-speed intelligent vehicle with machine vision,an improved algorithm of lane recognition is proposed.In order to obtain fine gradient images, graying,median filter,edge enhancement and optimal threshold are adopted to process images taken by experimental vehicle's CCD camera.Lane edge is detected according to its feature model by an improved Hough transformation.By focusing on area of interest(AOI) in pretreatment and detection,processing time is dramatically reduced.Moreover,the reliability of lane recognition is improved. The experimental result shows that this algorithm is of high efficiency,reliability and robustness.

Image Denoise Based on Soft-Threshold and Edge Enhancement

Abstract: In order to eliminate noise and preserve the edge and texture detail in image, this article proposes a method of image denoise based on soft-threshold and edge enhancement. To enhance edge, first we use the canny edge detection operator to detect the feature of the image, then we preprocess the edge image with a flat operator, next we use stationary wavelet transform to process the processed edge image and noisy image, then we add these wavelet coefficients at the corresponding level, so we can use the soft threshold denoise technology to eliminate the noise. Since the feature is enhanced before soft threshold denoise, the feature can be preserved well. From the result we can see that comparing to the wiener filter, this denoise method has visually pleasing image and the PSNR is improved. Comparing the traditional soft threshold denoise technology, this method has 1-2dB improvement in PSNR.

System and method for reducing halo effect in image enhancement

Abstract: A method of enhancing an image, comprising providing an image having luminescence and at least one boundary, determining locations each of the at least one boundary in the image, computing an image enhancement technique having a gain for application to the image, and adjusting the gain of the image enhancement based on the luminescence values of the image near the boundary locations.