Showing papers on "Edge enhancement published in 2003"

Gray and color image contrast enhancement by the curvelet transform

Abstract: We present a new method for contrast enhancement based on the curvelet transform. The curvelet transform represents edges better than wavelets, and is therefore well-suited for multiscale edge enhancement. We compare this approach with enhancement based on the wavelet transform, and the multiscale retinex. In a range of examples, we use edge detection and segmentation, among other processing applications, to provide for quantitative comparative evaluation. Our findings are that curvelet based enhancement out-performs other enhancement methods on noisy images, but on noiseless or near noiseless images curvelet based enhancement is not remarkably better than wavelet based enhancement.

Neural edge enhancer for supervised edge enhancement from noisy images

Abstract: We propose a new edge enhancer based on a modified multilayer neural network, which is called a neural edge enhancer (NEE), for enhancing the desired edges clearly from noisy images. The NEE is a supervised edge enhancer: Through training with a set of input noisy images and teaching edges, the NEE acquires the function of a desired edge enhancer. The input images are synthesized from noiseless images by addition of noise. The teaching edges are made from the noiseless images by performing the desired edge enhancer. To investigate the performance, we carried out experiments to enhance edges from noisy artificial and natural images. By comparison with conventional edge enhancers, the following was demonstrated: The NEE was robust against noise, was able to enhance continuous edges from noisy images, and was superior to the conventional edge enhancers in similarity to the desired edges. To gain insight into the nonlinear kernel of the NEE, we performed analyses on the trained NEE. The results suggested that the trained NEE acquired directional gradient operators with smoothing. Furthermore, we propose a method for edge localization for the NEE. We compared the NEE, together with the proposed edge localization method, with a leading edge detector. The NEE was proven to be useful for enhancing edges from noisy images.

Classifying color edges in video into shadow-geometry, highlight, or material transitions

Abstract: We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained labeling color transitions into one of the following types: 1) shadow-geometry, 2) highlight edges, and 3) material edges. The proposed method is empirically verified on images showing complex real world scenes.

Quantification of the effect of system and object parameters on edge enhancement in phase-contrast radiography.

Abstract: The purpose of this study was to evaluate the effects of system parameters (focal spot size, tube voltage, geometry, detector resolution, and imagenoise) and object characteristics (edge gradient/shape, composition, thickness, and overlying attenuating material) upon the edge enhancement effect in phase-contrast radiography. Each variable of interest was adjusted and images of a 3 mm lucite phantom were obtained with the other variables remaining constant. A microfocus x-ray source coupled to a CCD camera with an intensifying screen was used to acquire the digital images. Two parameters of image analysis were used to quantify the effects. The edge enhancement index (EEI) was used to measure the absolute degree of edge enhancement, while the edge enhancement to noise ratio (EE/N) was used to measure the conspicuity of the edge enhancement relative to imagenoise. Little effect on EEI was seen from tube voltage, object thickness, overlying attenuating material, while focal spot size and system geometry demonstrated measurable effects upon the degree of edge enhancement. It was also shown that while the edge enhancement effect over straight edges is highly dependent upon how the edge aligns with the x-ray beam, rounded edges, which better model biological objects, do not suffer from this dependence and the EEI reaches its maximal level at any alignment. Decreasing detector resolution diminished the EEI slightly, but even with pixel sizes of 0.360×0.360 mm edge enhancement effects were readily visible. The effect of imagenoise on EE/N was evaluated using different exposure times showing an expected improvement with longer exposure time with EE/N approaching a plateau at 5 min. Many of the parameters that will go into the design of a future PC-R imagingsystem have been quantified in terms of their effect on the degree of edge enhancement in the acquired image. These results, taken together, indicate that either a specimen or even clinical breast imagingsystem could be created with currently available technology. The major limitation to a clinical system would be the low x-ray flux from the microfocal x-ray source.

Adaptive image denoising and edge enhancement in scale-space using the wavelet transform

Abstract: This paper proposes a new method for image denoising with edge preservation and enhancement, based on image multi-resolution decomposition by a redundant wavelet transform. At each resolution, the coefficients associated with noise and the coefficients associated with edges are modeled by Gaussians, and a shrinkage function is assembled. The shrinkage functions are combined in consecutive resolutions, and geometric constraints are applied to preserve edges that are not isolated. Within the proposed framework, edge related coefficients may be enhanced and denoised simultaneously. Finally, the inverse wavelet transform is applied to the modified coefficients. This method is adaptive, and performs well for images contaminated by natural and artificial noise.

Nonlinear multiresolution gradient adaptive filter for medical images

Abstract: We present a novel method for intra-frame image processing, which is applicable to a wide variety of medical imaging modalities, like X-ray angiography, X-ray fluoroscopy, magnetic resonance, or ultrasound. The method allows to reduce noise significantly - by about 4.5 dB and more - while preserving sharp image details. Moreover, selective amplification of image details is possible. The algorithm is based on a multi-resolution approach. Noise reduction is achieved by non-linear adaptive filtering of the individual band pass layers of the multi-resolution pyramid. The adaptivity is controlled by image gradients calculated from the next coarser layer of the multi-resolution pyramid representation, thus exploiting cross-scale dependencies. At sites with strong gradients, filtering is performed only perpendicular to the gradient, i.e. along edges or lines. The multi-resolution approach processes each detail on its appropriate scale so that also for low frequency noise small filter kernels are applied, thus limiting computational costs and allowing a real-time implementation on standard hardware. In addition, gradient norms are used to distinguish smoothly between “structure” and “noise only” areas, and to perform additional noise reduction and edge enhancement by selectively attenuating or amplifying the corresponding band pass coefficients.

A simple and efficient watermarking technique based on JPEG2000 codec

Abstract: We propose an effective watermarking scheme to embed and extract based on the JPEG2000 codec process. Our embedding algorithm applied the Torus Automorphisms technique to break up the watermark, which were then embedded into the bitstreams after the JPEG2000 quantization step but prior to entropy coding. Distortion reduction technique was used on the compressed image to lessen image degradation caused by embedding. Our watermark scheme is simple and easy to implement. Furthermore, our scheme is robust to attacks like blurring, edge enhancement, mosaic, and more.

Image processing method

Abstract: PROBLEM TO BE SOLVED: To effectively suppress the generation of a pseudo contour and perform display with high image quality The input image data is subjected to resolution conversion processing (4) accompanied by an increase in the number of gradations, and the input image data is subjected to edge enhancement processing (5) accompanied by an increase in the number of gradations In the image processing method for performing dither processing (7) accompanied by a decrease in the number of gradations per pixel on the processed image data, a combination of a parameter relating to the direction of resolution conversion and a parameter relating to the size of the edge enhancement Accordingly, when the resolution conversion is enlargement or the edge enhancement is relatively weak, the number of pseudo gradations is determined so that the number of pseudo gradations in the dither processing is increased [Selection] Figure 1

Method and apparatus for enhancement of digital image quality

Abstract: A digital image quality enhancement method and apparatus convert RGB color data of a pixel of interest into color data having a brightness component and a saturation component, and segment the pixel of interest into a background pixel, an image pixel, or a text pixel using the brightness component and the saturation component. The method and apparatus label the pixel of interest as a text area, a background area, or an image area using history information regarding the pixel of interest, where the history information is a number of successive background pixels or image pixels before the pixel of interest. An image quality of the pixel of interest is enhanced to degrees corresponding to the area labeled and the method determines whether the pixel of interest is a final pixel of which an image quality is to be improved.

Image processing apparatus and method

Abstract: An edge amount detector detects an edge amount from RGB signals, and a filter processor synthesizes an output for edge enhancement with an output for smoothing at a proportion based on the detected edge amount Another edge amount detector detects an edge amount of a black component from CMY signals, and an ink generator/undercolor remover changes an ink generation rate according to the detected edge amount

Method and apparatus for image detail enhancement without zigzagged edge artifact

Abstract: A method and system for detecting slant edge areas in an image comprising a plurality of pixels, and for preventing zigzagged slant edge artifacts in an image detail enhancement process. Image pixels that belong to a slant image edge are detected and gain suppression factors are determined for the detected pixels. The image is detail enhanced while selectively reducing enhancement of the detected image pixels relative to enhancement of other image pixels based on the gain suppression factors.

Image enhancement using warping technique

Abstract: An image enhancement algorithm based on a warping technique is presented. The warping map is chosen in order to sharpen the edges of the image. In contrast to other algorithms, enhancement is performed without introducing overshoot in sharp edges and without amplifying the noise present in the original image.

Morphological operations by locally variable structuring elements and their applications to region extraction in ultrasound images

Abstract: In this paper, we define a new adaptive morphological operation, in which the value of a structuring element varies adaptively depending on the local intensity information of the processing image of interest. We prove that the proposed adaptive morphological operation has almost the same mathematical structure and properties as the conventional ones have. There are many useful functions in the method. Among them are the opening and closing, which implement both smoothing of the image and emphasizing of the edges at a time. Conventional opening operation has a smoothing function but not both. Applying our method to relatively unclear images such as ultrasound ones with speckle noise, its usefulness can be found in extracting regions. We also discuss parameter setting, and its enhancement effect together with experimental results is demonstrated. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(3): 33–43, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10196

A System for Real-Time Endoscopic Image Enhancement

Abstract: During endoscopic operations the surgeon works without direct visual contact to the operation area. The image of the operation situs is displayed on a monitor. Currently, only hardware based image enhancement methods are used (e. g., white balance) and often only once at the beginning of an operation. In this contribution we describe a system for real-time endoscopic image enhancement: a typical video-endoscopic system was extended by a computer and a second monitor. Thus the enhanced and the original image can be displayed at the same time. The implemented image enhancement methods (temporal filtering, undistortion and color normalization) were evaluated by 14 surgeons and the results showed that the enhanced images were preferred. The system was already used during a real operation.

Method and apparatus for improving picture sharpness

Abstract: A method for improving the sharpness of pictures contained in a video signal comprises the steps of: a) processing said pictures on the basis of a step/edge enhancement algorithm to obtain step/edge enhanced pictures, b) processing said pictures on the basis of a texture enhancement algorithm to obtain texture enhanced pictures, and mixing said step/edge enhanced pictures with said texture enhanced pictures to obtain a video signal containing sharpness-improved pictures, wherein steps a) and b) are performed in dependence of motion information being related to said pictures.

Apparatus for and method of edge enhancement in image processing

Abstract: An apparatus for and a method of simultaneously performing edge detection and enhancement without any additional memory storage include an image sensor sensing an image to output image data, a line buffer receiving the image data to output the image data, a register storing the image data transmitted from the line buffer, an interpolation unit performing an interpolation operation on the image data received from the register, an edge detection unit performing an edge detection operation on the image data received from the register to output an edge detection signal in parallel to the interpolation operation of the interpolation unit according to a selection signal representing a pattern of the image data stored in the register, and an edge enhancement unit enhancing an output of the interpolation unit according to the edge detection unit of the edge detection unit.

Adaptive unsharp masking method based on region segmentation

Abstract: A adaptive unsharp masking method based on region segmentation is presented aiming at the defects of linear unsharp masking. The input image is divided into homogeneous areas, medium contrast areas and large contrast areas by the local variance of image pixels. Base on the area type to which image pixel (x,y) belongs, the local activity gain factor α(x,y) and the desired output local activity Hd(x,y) are determined adaptively, and the enhancement factor K(x,y) is derived. A X_ray chest image is processed with the proposed method and other unsharp masking methods. The results show that good capabilities of edge enhancing and noise suppressing are achieved by the proposed method.

Perceptual image processing for digital edge linking

Abstract: This paper presents two methods of digital edge linking that have a reasonable correlation with psychological properties employed by human users. In the first method, each endpoint is linked to the point judged to be its best match under the criteria of alignment and proximity. The second method uses two edge images that have undergone hysteresis: a " high image" which uses high thresholds, and a "low image" which uses low thresholds. The idea is to use the high image as a guide for deciding which edges from the low image to express in the output image. Both methods achieve moderate improvements in restoring "gappy" edges in the sample images presented.

Nanostructure array of coupled RTDs as cellular neural networks

Abstract: The processing capabilities of a proposed nanoelectronic device are investigated. The device is considered as a global dynamical system with local circuit model components. The system equations and the corresponding network model are presented. The characteristics of this network model are compared with the cellular neural networks. Certain characteristics of the network are analysed theoretically and demonstrated with circuit-system level simulations. As a novel property, it is shown that the single layer nanodevice network structure is a basic reaction–diffusion system and it is capable of autowave propagation. Furthermore, the same network structure exhibits several image processing capabilities like image smoothing, edge enhancement, and horizontal or vertical line detection using simple arrangements of the device parameters. Copyright ©2003 John Wiley & Sons, Ltd.

Image processing apparatus, image processing method, image processing program, and storage medium

Abstract: A domain block image is extracted from an original image by a domain block extracting section, and the domain block image is classified by a domain block classifying section. A range block extracting section extracts a range block image larger than the domain block image from the original image, and a reduced range block forming section reduces the range block image at the same size as the domain block image. A similarity degree judging section judges a similarity degree between the reduced range block image and the domain block image, and an improved domain block forming section performs a conversion of pixel values with respect to the reduced range block image in accordance with this similarity degree. Further, an edge enhancement processing section executes an edge enhancement processing as to the step edge portion so as to obtain an improved domain block image.

Digital enhancement of night vision and thermal images

Abstract: : Low image contrast limits the amount of information conveyed to the user With the proliferation of digital imagery and computer interface between man-and-machine, it is now viable to consider digitally enhancing the image before presenting it to the user, thus increasing the information throughput. This thesis explores the effect of the Contrast Limited Adaptive Histogram Equalization (CLAHE) process on night vision and thermal images With better contrast, target detection and discrimination can be improved. The contrast enhancement by CLAHE is visually significant and details are easier to detect with the higher image contrast. Analyzing the image frequency response reveals increases in the higher spatial frequencies. As higher frequencies correspond to image edges, the power increase is viewed as corresponding to edge enhancement and hence, an increase in visible image details. This edge enhancement is perceived as improvement in image quality. This is further substantiated by a subjective testing, where a majority of human subjects agreed that CLAHE-enhanced images are more informative than the original night vision images.

Noise reducing apparatus

Abstract: First and second noise detecting circuits detect whether image data output from a signal processing circuit includes noise If the image data includes noise, first and second noise reducing circuits reduce the noise An edge extracting circuit extracts edge data from the first image data in which noise has been reduced An adding circuit adds the edge data and second image data, which has been output by the second noise reducing circuit, and outputs the resultant data Even though edge enhancement is applied, noise is not enhanced but noise is reduced

Simulation Comparison of Lateral Inhibition Models In Image Enhancement

Abstract: Lateral Inhibition (LI) networks has been used in engineering broadly. When used in image contrast enhancement, the followings should be taken into consideration to get the optimal outcoming: LI model, distribution of inhibition intensity and size of inhibition fields. According to the classification rules of LI mathematics models, a new model is presented based on those that have been founded on physiological experiments, and double-peak Gauss curve is selected as a distribution of inhibition intensity. The differences among these mathematics models and their arguments are discussed on the aspects of running speed and edge enhancement by computer simulation.

An efficient noise removal and edge preserving convolution filter

Abstract: A computationally efficient method for image enhancement based upon convolution kernels is introduced. The proposed convolution kernel is a linear combination of a uniform and Sobel kernel and combines the desired properties of both. Simulation results on a benchmark image support the analysis.

A new wavelet-based method for contrast/edge enhancement

Abstract: Contrast enhancement is usually achieved by histogram equalizing image pixel gray-levels in the spatial domain to redistribute them uniformly. Meanwhile, edge enhancement attempts to emphasize the fine details in the original image. But in the spatial domain it is hard to selectively enhance details at different scales. Moreover, in the spatial domain, applying contrast and edge enhancement techniques in different orders may yield different enhancement results. To overcome the above spatial domain enhancement issues, a new wavelet-based image enhancement method is proposed. The proposed method histogram-equalizes the approximation-coefficients. At the same time, it high-boost filters the detail-coefficients at selected resolution levels separately. The experiments show that utilizing the proposed method can achieve robust contrast and edge enhancement. Moreover, the computation cost in the wavelet domain is less than that in the spatial domain. This is especially true when considering that currently most images are already wavelet-compressed (the current JPEG 2000 standard is a wavelet based scheme).

4x4 Pixel-based edge detection and edge enhancement without line buffer overhead

Abstract: A digital image upscaling system enhances the visual quality of enlarged images by detecting diagonal edges and applying an appropriate scaling algorithm, such as a rotated bilinear scaling process, to output pixels associated with those edges. The rotated bilinear scaling process involves detecting diagonal edges and specifying a new frame of reference rotated 45° from the original frame of reference, and then selecting a rotated pixel set based on the new frame of reference. Bilinear interpolation in the new frame of reference using the rotated pixel set provides improved pixel data for the output pixel. Output pixels found not to be associated with diagonal edges are processed using standard bilinear interpolation.

Image processor and image processing method

Abstract: PROBLEM TO BE SOLVED: To provide an image processor and an image processing method capable of achieving a high-quality display video image by appropriately controlling processing for reducing a motion blur in the displayed video image caused by the time integral effect of an image sensor. SOLUTION: An image display device has; a motion detection section 1 for detecting the amount of motion in an input image signal; and an edge enhancement section 2 for performing edge enhancement processing to the input image signal. The image display device increases the degree of edge enhancement in the edge enhancement processing to a region having a large amount of motion in the input image signal. The image display device also has a control section 4 for controlling the edge enhancement section 2 so that the degree of edge enhancement in the edge enhancement processing is reduced or no edge enhancement processing is performed, when it is recognized that a high-frequency component included in the input image signal has not attenuated in a process of input image signal generation even in a region having a large amount of motion in the input image signal, based on picture tone mode information indicating a picture tone mode selected and designated by a user. COPYRIGHT: (C)2009,JPO&INPIT