Showing papers on "Edge enhancement published in 2004"

A non-parametric blur measure based on edge analysis for image processing applications

Abstract: A nonparametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining the standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.

Image processing method and apparatus

Abstract: An image processing method includes: discriminating between a still picture area and a motion picture area in an input image; enhancing edges with a quantity of edge enhancement larger in the motion picture area than in the still picture area; and outputting the input image having the enhanced edges. The output having the enhanced edges is displayed on a display unit.

An edge enhancement process and system

Abstract: An edge enhancement system, including a selective edge controller for determining one or more properties of an edge of image data, and for generating one or more weighting factors on the basis of properties of the edge; and a scaling module for scaling an edge enhancement signal by the weighting factors to control the degree of edge enhancement. The image data may represent a still or moving (i.e., video) image. A max-min search circuit determines maximum and minimum turning points closest to the center of the data processing window and that are located on opposing sides of the window, to determine values and locations of maximum and minimum pixels of the edge. An edge-directed pre-filtering circuit reduces the amplification of edge fuzziness by smoothing close the edges vertical prior to enhancement. An aliasing protection circuit reduces the visibility of saw-tooth defects on predominantly horizontal diagonal edges.

A simple and efficient watermark technique based on JPEG2000 Codec

Abstract: In this paper we propose an effective watermark scheme for embedding and extracting based on the JPEG2000 Codec process. Our embedding algorithm applies the torus automorphisms (TA) technique to break up and scramble a watermark. The scrambled watermark was embedded into the quantized bitstreams of JPEG2000 before the entropy coding stage. Distortion reduction (DR) was applied to the compressed image to lessen image degradation caused by the embedding process. Our watermark scheme is simple and easy to implement. Furthermore, it is robust to attacks like blurring, edge enhancement, and other image processing manipulations.

Quantitative characterization of edge enhancement in phase contrast x-ray imaging.

Abstract: The aim of this study was to model the edge enhancement effect in in-line holography phase contrast imaging. A simple analytical approach was used to quantify refraction and interference contrasts in terms of beam energy and imaging geometry. The model was applied to predict the peak intensity and frequency of the edge enhancement for images of cylindrical fibers. The calculations were compared with measurements, and the relationship between the spatial resolution of the detector and the amplitude of the phase contrast signal was investigated. Calculations using the analytical model were in good agreement with experimental results for nylon, aluminum and copper wires of 50 to 240 microm diameter, and with numerical simulations based on Fresnel-Kirchhoff theory. A relationship between the defocusing distance and the pixel size of the image detector was established. This analytical model is a useful tool for optimizing imaging parameters in phase contrast in-line holography, including defocusing distance, detector resolution and beam energy.

Pulse-domain digital image processing for vision chips employing low-voltage operation in deep-submicrometer technologies

Abstract: A new architecture for pixel-level parallel image processing in the pulse domain for CMOS vision chips has been developed. Image processing such as edge enhancement, edge detection, and blurring are realized based on suppression and promotion of digital pulses; the pixel value is represented by the frequency of digital pulses by use of a pulse-frequency modulation (PFM) photosensor or that with an in-pixel 1-bit analog-to-digital converter. The proposed architecture is suitable for low-voltage operation in deep-submicrometer technologies because the image processing is implemented by 1-bit fully digital circuits with a small number of logic gates. The principles of the image processing are addressed. We have fabricated a 16 /spl times/ 16-pixel prototype vision chip. The relationship between illumination and the output pulse frequency is characterized. Step responses of the prototype vision chip for fundamental image processing operations show good agreement with those expected by correlation-based spatial filtering. A simple image binarization method specific to our architecture is also presented. The histograms of the intervals of the output pulses after image processing show multiple peaks, which indicates that averaging of the intervals is required for longer periods to achieve higher image-processing quality. To improve the linearity of pulse frequency dependence on illumination, usage of random clocks is discussed.

Method and apparatus for enhancing a digital image by applying an inverse histogram-based pixel mapping function to pixels of the digital image

Abstract: A method and associated device wherein an inverse histogram based pixel mapping step is combined with an edge enhancement step such as unsharp masking. In such an arrangement the inverse histogram based pixel mapping step improves the performance of the unsharp masking step, serving to minimize the enhancement of noise components while desired signal components are sharpened.

Image sharpening with region edge sharpness correction

Abstract: A system and process for improving image quality is described. The process uses an edge map to smooth colors based on at least one of how close a pixel is to an edge and the strength of the edge.

Modification of standard image compression methods for correlation-based pattern recognition

Abstract: Standard image compression algorithms may not perform well in compressing images for pattern recognition applications, since they aim at retaining image fidelity in terms of perceptual quality rather than preserving spectrally significant information for pattern recognition. New compression algorithms for pattern recognition are therefore investigated, which are based on the modification of the standard compression algorithms to simultaneously achieve higher compression ratio and improved pattern recognition performance. This is done by emphasizing middle and high frequencies and discarding low frequencies according to a new distortion measure for compression. The operations of denoising, edge enhancement, and compression can be integrated in the same encoding process in the proposed compression algorithms. Simulation results show the effectiveness of the proposed compression algorithms.

DSP based image processing for retinal prosthesis

Abstract: The real-time image processing in retinal prosthesis consists of the implementation of various image processing algorithms like edge detection, edge enhancement, decimation etc. The algorithmic computations in real-time may have high level of computational complexity and hence the use of digital signal processors (DSPs) for the implementation of such algorithms is proposed here. This application desires that the DSPs be highly computationally efficient while working on low power. DSPs have computational capabilities of hundreds of millions of instructions per second (MIPS) or millions of floating point operations per second (MFLOPS) along with certain processor configurations having low power. The various image processing algorithms, the DSP requirements and capabilities of different platforms would be discussed in this paper.

Systems and methods for image processing providing noise reduction and edge enhancement

Abstract: Image processing methods and systems for noise reduction and edge enhancement. A variation detector is provided to evaluate measures of edge existence in a plurality of predetermined directions within pixels of a video signal, and determine a control signal according to a level of variation on the measures of edge existence. A noise reduction circuit and edge enhancement circuit filter and edge enhance the video signal, respectively, according to the control signal.

Edge enhancement system and method and imaging system

Abstract: A plurality of bandpass filters extract high frequency components of a digital image signal sampled every predetermined unit, thus generating a plurality of high frequency signals. The high frequency signals are added to produce a resultant high frequency signal. On the basis of the value of the resultant high frequency signal, the maximum value or minimum value detected from the high frequency signals is selected. The resultant high frequency signal and the selected maximum or minimum value are added according to determined weights, so that an enhancement signal is generated. Edge enhancement is performed using the enhancement signal.

A simple edge-weighted image enhancement filter using wavelet scale products

Abstract: In this paper, we propose a non-linear image enhancement filter for noisy images. Unsharp masking that is widely used for image enhancement amplifies image contrast by adding the high-frequency component that is obtained by a linear high-pass filter from an input image. The linear high-pass filter of the unsharp masking also emphasizes noises that appear in the input image. In order to avoid the emphasis of the noises, weighted unsharp masking techniques have been proposed. In these methods, the high-frequency component is defined as a product between a weighting function of which modulus increases around image edges and the linear high-pass filter output. To improve the noise suppression property of the weighted unsharp masking, we introduce wavelet scale products to the weighting function. The weighting function of the proposed method is defined as the linear combination of the squared of a wavelet transform and the product of the wavelet transforms at different scales. We specify the parameter of the weighting function based on the edge enhancement property and the noise amplification property. The statistical analysis of the noise amplification shows that the proposed method can reduce the noise variance to about 1/5 of the gradient-based weighted unsharp masking filter. Examples of image enhancement and a comparison between the other weighted unsharp masking are also shown.

Low-complexity comprehensive labeling and enhancement algorithm for compound documents

Abstract: We present a multiresolutional algorithm that segments a compound document and uses the results of the segmentation for document enhancement in copier applications. The document is initially segmented into halftone and nonhalftone areas. Based on this segmentation the location of the edges due to text, graphics, and images (and not due to halftone dots) are detected on halftone as well as on nonhalftone portions. We further detect constant-tone regions within nonhalftone areas for subsequent bleed-through removal applications. Edge enhancement on detected edges and descreening on detected halftones are carried out. The algorithm can detect general halftones over regions of arbitrary sizes and shapes, and it can be straightforwardly adjusted for operation at various dpi resolutions. We obtain high detection probabilities on compound multilingual documents containing halftones and fine text. The proposed enhancement stage is tolerant of segmentation errors providing robust performance for the remaining problem cases. Our main contribution is the accomplishment of these tasks with a single pass algorithm that is computationally very simple and that requires less than 1% of full page memory, with active memory requirements less than 0.02% of full page memory. The operation of the algorithm can be imagined as a very thin line (of thickness the size of a "full-stop" in 11 pt text) that rapidly scans an input page while simultaneously producing an output page.

Image processor and image processing method

Abstract: PROBLEM TO BE SOLVED: To obtain images of edge enhancement strength optimum for both compressed stored data and display data simultaneously in real time. SOLUTION: In an imaging unit 1, digital image data are produced from a video signal outputted from an imaging device 11 by a signal processing section 12, edge enhancement is performed by an edge enhancement section 13, zoom processing is performed by a zooming section 14 and the image data are inputted to a display unit 2 and a compression and storage unit 3, respectively. In the display unit 2, a resolution is converted by a resolution conversion section 21, edge enhancement is performed by an edge enhancement section 22, a driving signal is generated by a display control section 23, and the image data are displayed on a display 24. In the compression and storage unit 3, edge enhancement is performed by an edge enhancement section 31, and the image data are compressed by a compression section 32 and stored in a storage section 33. A control unit 4 adaptively controls edge enhancement strengths in the edge enhancement sections 13, 22 and 31 while being linked with a zoom magnification power in the zooming section 14. COPYRIGHT: (C)2006,JPO&NCIPI

Scale-based image enhancement using modified anisotropic diffusion filter

Abstract: We propose a scale-based image enhancement method using a modified anisotropic diffusion filter that employs sensor noise estimation and scale space methods based on a minimum reliable scale. Based on the relationship between the local gradient and the critical value function, an image is classified into various scales representing the region's complexity. The degree of enhancement is then adjusted according to each region's complexity. When compared to the existing linear unsharp masking, adaptive unsharp masking, and warping-based methods, the proposed algorithm produces negligible noise amplification in homogeneous regions and superior edge enhancement.

Photorefractive edge-enhancement and its application for pattern recognition

Abstract: Coupling theory is employed to analyze the coupling gain and a novel optical system is presented for image edge-enhancement by employing photorefractive two-wave coupling in BaTiO3 crystal, in which the ordinarily discarded background light is recycled as the pump source to amplify the signal light. Further, we demonstrate the principle of optical correlation and compare the discrimination capability of two kinds of correlators by computer simulation, in one of which input images are edge-enhanced and in the other the ones do not experience edge-enhancement. At last, we draw a conclusion that edge-enhancement preprocessing can improve discrimination capability effectively.

Image taking apparatus, and a method of controlling an edge enhancing level of an original image signal

Abstract: According to the image taking apparatus and the method of controlling an edge enhancing level of an original image signal, as the electronic zooming rate for the original image signal increases, an amplitude level of the edge signal decreases in a direction contrary to the increase of the electronic zooming rate, and thereby, an edge enhancing level of the edge-enhanced image signal is automatically suppressed. Accordingly, even though zooming processing is applied to the edge-enhanced image signal, it is able to obtain an enlarged image signal having natural edges by suppressing excess enlargement of the edge signal added to the original image signal.

Image edge enhancement system and method

Abstract: We describe and claim an edge enhancement system and method. The edge enhancement system includes an edge enhancement circuit to enhance a portion of image data with enhancement data determined from the image data, and a panel to display the enhanced image data. The edge enhancement circuit includes a receiver to receive the image data, a determining circuit to determine enhancement data from the image data, and an enhancing circuit to enhance a portion of the image data with the enhancement data. In an embodiment, the enhancing circuit mathematically manipulates a portion of the image data with the enhancement data. In another embodiment, the enhancing circuit replaces a portion of the image data with the enhancement data.

A mathematical morphological method to thin edge detection in dark region

Abstract: The performance of image segmentation depends on the output quality of the edge detection process. Typical edge detecting method is based on detecting pixels in an image with high gradient values, and then applies a global threshold value to extract the edge points of the image. By these methods, some detected edge points may not belong to the edge and some thin edge points in dark regions of the image are being eliminated. These eliminated edges may be with important features of the image. This paper proposes a new mathematical morphological edge-detecting algorithm based on the morphological residue transformation derived from dilation operation to detect and preserve the thin edges. Moreover, this work adopts five bipolar oriented edge masks to prune the miss detected edge points. The experimental results show that the proposed algorithm is successfully to preserve the thin edges in the dark regions.

Segmenting lumbar vertebrae in digital video fluoroscopic images through edge enhancement

Abstract: Video fluoroscopy provides a cost effective way for the diagnosis of low back pain. Backbones or vertebrae are usually segmented manually from fluoroscopic images of low quality during such a diagnosis. In this paper, we try to reduce human workload by performing automatic vertebrae detection and segmentation. Operators need to provide the rough location of landmarks only. The proposed algorithm would perform edge detection, which is based on pattern recognition of texture, along the snake formed from the landmarks. The snake would then attach to the edge detected. Experimental results show that the proposed system can segment vertebrae from video fluoroscopic image automatically and accurately.

Image decomposition for selective encryption and flexible network services

Abstract: We propose a novel image and video preprocessing technique (edge and residuum decomposition - ERD) that mainly concerns the decomposition of the image into three separate components: edge location; gray-tone or color inside the edges; residuum "smooth" image. While the residuum image is compatible with any natural-image encoder, new algorithms and solutions are introduced to achieve a compressed description of the edge-based information; the overall occupancy is comparable to that yielded by traditional image and video encoders. Both qualitative and quantitative results are shown, as well as an analysis of the separate components. Since all the components (edge position, edge color and residuum) are needed to completely describe the image, whilst some of them are particularly critical to recognize (and "preview") it, the proposed solution enables new encoding services, mainly selective encryption; just hiding edge positions leaves a perceptually meaningless image unencrypted.

Unsharp masking based on the multiscale gradient planes

Abstract: In this paper, control of emphasis by the multiscale brightness gradient is introduced for unsharp masking. This provides an improved image emphasis method for realizing effective emphasis for any image with superposed Gaussian noise and low-contrast images. Unsharp masking is a method of obtaining an enhanced image by applying a high-pass filter to blurred images so that the obtained high-pass components are superposed on the original image. However, unsharp masking has the deficiency that the noise is also enhanced due to its principle of operation when noise is superposed on the blurred image. In order to alleviate this problem, this paper proposes a characteristic quantity of image edges (edge information) using the amplitude shift between the scales of the multiscale brightness gradient, and applies it to the control of the emphasis of unsharp masking. The proposed edge information takes a positive value on the image edge and the amplitude is proportional to the smoothness and brightness difference of the edges. Since the proposed edge information takes a positive value at the smoothed edges regardless of the variance of the superposed Gaussian noise and the image contrast, it is possible to reduce the effect of noise in the emphasis result by controlling the image emphasis by discriminating positive or negative values. In the experiment, the proposed edge information is introduced into unsharp masking using a fuzzy rule and into third-order unsharp masking. The effectiveness of the proposed edge information is confirmed by image emphasis. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(4): 40–54, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10113

Device, method and program for image processing, and storage medium

Abstract: PROBLEM TO BE SOLVED: To provide an image processing device which can have an image of high quality by comprehensively improving deterioration components of image blur, jaggy appearance, noise and so on using a single technique, and also to provide an image processing method therefor. SOLUTION: A domain block extractor 31 extracts a domain block image from an original image, and a main block classifier 32 classifies the type of the extracted image. When the extracted image is of a step edge or noise type, a range block extractor 33 extracts a range block image larger than the domain block image from the original image, and a reduced range block generator 34 reduces the extracted range block image to the same size as the domain block image. A similarity decider 35 decides a similarity between the reduced range block image and the domain block image. An improved domain block generator 36 converts the number of pixels in the reduced range block image according to the decided similarity. With respect to the step edge type, an edge enhancer 37 applies edge enhancement thereto to obtain an improved domain block image. COPYRIGHT: (C)2004,JPO

Gradient Pile up Algorithm for Edge Enhancement and Detection

Abstract: Edge detection plays a fundamental role on image processing. The detected edges describe an object contour that greatly improves the pattern recognition process. Many edge detectors have been proposed. Most of them apply smooth filters to minimize the noise and the image derivative or gradient to enhance the edges. However, smooth filters produce ramp edges with the same gradient magnitude as those produced by noise. This work presents an algorithm that enhances the gradient correspondent to ramp edges without amplifying the noisy ones. Moreover, an efficient method for edge detection without set a threshold value is proposed. The experimental results show that the proposed algorithm enhances the gradient of ramp edges, improving the gradient magnitude without shifting the edge location. Further, we are testing the implementation of the proposed algorithm in hardware for real time vision applications.

Speckle Reduction and Edge Enhancement of NDE C‐Scan Images Using ICA

Abstract: A new speckle reduction and edge enhancement method for ultrasonic NDE images is proposed. Our method is based on Independent Component Analysis (ICA). Firstly, we use FastICA algorithm to estimate the basis images. Then a demixing transform of the original image is employed. In terms of the characteristic of NDE images, we assume that “speckle noise” and “true signal” come from different signal sources, or signal spaces, and then use a classifier to classify these basis images. Based on the classification result, we design our nonlinear filter for each independent component and obtain our restored image after a mixing transformation. Finally, we compare our method with median filtering and Wiener filtering. The experimental results demonstrate that the proposed method achieves a better performance improvement.

Image processor capable of edge enhancement in saturated region

Abstract: An image processing device includes a data zone expansion circuit and an image processing circuit. The data zone expansion circuit receives input data, increases a number of data bits of the input data, and provides data with the increased number of data bits. The image processing circuit performs image processing on the data with the increased number of data bits.

Content based image public watermarking

Abstract: In this paper, a content based image public watermarking technique which operates in DCT domain is proposed. First, the 8×8 DCT sub-blocks of the host image are rearranged into a Hilbert sequence in Hilbert scanning order, then two neighboring sub-blocks in the Hilbert sequence is pseudo-randomly selected by using chaotic sequences. Then a watermark with visually recognizable pattern is embedded into the original image by changing the polarity of the corresponding middle-frequency coefficients in the two chosen neighboring sub-blocks, and the watermark is adapted to the image by exploiting the masking characteristics of the human visual system (HVS), thus ensuring the watermark invisibility, and the watermark don't need the original image. The experimental results show that the proposed algorithm in this paper is robust to common signal processing techniques and some geometric distortions, such as cropping, scaling and rotation. Especially, it achieves high robustness under signal enhancement operations, such as sharpening, contrast enhancement, edge enhancement and histogram equalization.