Showing papers on "Edge enhancement published in 2016"

Guided Image Contrast Enhancement Based on Retrieved Images in Cloud

Abstract: We propose a guided image contrast enhancement framework based on cloud images, in which the context- sensitive and context-free contrast is jointly improved via solving a multi-criteria optimization problem. In particular, the context-sensitive contrast is improved by performing advanced unsharp masking on the input and edge-preserving filtered images, while the context-free contrast enhancement is achieved by the sigmoid transfer mapping. To automatically determine the contrast enhancement level, the parameters in the optimization process are estimated by taking advantages of the retrieved images with similar content. For the purpose of automatically avoiding the involvement of low-quality retrieved images as the guidance, a recently developed no-reference image quality metric is adopted to rank the retrieved images from the cloud. The image complexity from the free-energy-based brain theory and the surface quality statistics in salient regions are collaboratively optimized to infer the parameters. Experimental results confirm that the proposed technique can efficiently create visually-pleasing enhanced images which are better than those produced by the classical techniques in both subjective and objective comparisons.

A Hybrid Approach Using Sobel and Canny Operator for Digital Image Edge Detection

Abstract: Edge Detection is a very essential part in digital image processing. In case of applications which require object information or feature extraction in an image, edge detection can play a vital role. Edge occurs where there is discontinuity or a sharp change in the intensity function. Now there are many operators for edge detection, but the challenge is to get better results from the existing system. This paper represents a hybrid approach which combines the Sobel and Canny edge detectors. It also uses a median filter to remove the salt and pepper noise from the image which consequently smoothen the image and edges can be detected easily. A comparison has also been shown between the hybrid approach with median filter and without median filter. The comparative study shows that using median filter shows enhanced result. As it filters the noise from the image, the accuracy of edge detection improved and achieved ideal effect.

Image edge enhancement using Airy spiral phase filter.

Abstract: The isotropic and anisotropic image edge enhancements by employing Airy spiral phase filters are proposed and demonstrated. The coherent spread functions of the image systems are derived from transmittance functions of their corresponding filters. In the isotropic method, the distributions of the coherent spread function with the radius of the main ring ρ0 and the scaled parameter w0 are numerically analyzed. It is found that the width of the main lobe determining the resolution decreases with the increased ρ0, and the amplitudes of the side lobes connecting with the contrast fluctuate with w0. Compared with the existing spiral phase filters, higher contrast and resolution can be achieved by adjusting the two parameters in the Airy spiral phase filter. Moreover, an off-axis Airy spiral phase filter by controlling the center position (ρ0,ϕ1) is designed and employed to implement anisotropic edge enhancement. In the experiments, two methods of image edge enhancement have been verified by using the amplitude-contrast and phase-contrast objects.

Edge enhancement control in linear arrays of ungated field emitters

Abstract: In arrays of ungated field emitters, the field enhancement factor of each emitter decreases as the distance between the emitters decreases, an effect known as screening. At the edge of these arrays, emitters experience reduced screening, leading to higher field enhancement factors than emitters at the array center, causing nonuniform emission across the array. Here, we consider this effect in linear arrays of ungated field emitters spaced at distances comparable to their heights, which is the regime that generally maximizes their average current density. A Line Charge Model is used to assess the degree to which these edge effects propagate into the array interior, and to study the impact of varying the height, location, and tip radius of emitters at the ends of an array on the edge enhancement. It is shown that each of these techniques can accomplish this edge enhancement control, but each has advantages and disadvantages that will be discussed.

Vectorial optical vortex filtering for edge enhancement

Abstract: We propose to use a super-structured waveplate (called an S-waveplate) for vectorial optical vortex filtering, and experimentally demonstrate the radial Hilbert transform and selective edge enhancement. Based on the Jones calculus of polarization states and Fourier analysis, we calculate and analyze the point spread function of an optical 4-f system including an S-waveplate filter having the vectorial vortex of topological charge 1 (TC = 1). Numerical simulations and optical experiments demonstrate that a vectorial optical vortex filter can be used to implement selective edge enhancement with an analyzer before the output plane. The edge enhancement can be obtained even when the center of the filter is off-axis or the illuminating light is non-monochromatic.

Edge enhancement of potential field data using spectral moments

Abstract: Edge enhancement in potential-field data helps geologic interpretation, where the lineaments on the potential-field frequently indicate subsurface faults, contacts, and other tectonic features. Therefore, a variety of edge-enhancement methods have been proposed for locating edges, most of which are based on the horizontal or vertical derivatives of the field. However, these methods have several limitations, including thick detected boundaries, blurred response to low-amplitude anomalies, and sensitivity to noise. We have developed the spectral-moment method for detecting edges in potential-field anomalies based on the second spectral moment and its statistically invariable quantities. We evaluated the spectral-moment method using synthetic gravity data, EGM-2008 gravity data, and the total magnetic field reduced to the pole. Compared with other edge-enhancing filters, such as the total horizontal derivative (TDX), profile curvature, curvature of the total horizontal gradient amplitude, enhancement...

Human face image beautifying method

Abstract: The invention relates to a human face image beautifying method. The method is characterized in that a, a human face area of an image to be processed can be determined by adopting a human face identifying algorithm, and the contour extraction of the detected human face area can be carried out, and then the human face area can be separated from the image background; b, the skin color area of the image can be extracted by adopting the color threshold segmentation; c, the image buffing processing of the extracted skin color area can be carried out; and d, the emergence processing and the edge enhancement of the image edges can be carried out.

Contrast enhancement in microscopy of human thyroid tumors by means of acousto-optic adaptive spatial filtering.

Abstract: We report a method for edge enhancement in the images of transparent samples using analog image processing in coherent light. The experimental technique is based on adaptive spatial filtering with an acousto-optic tunable filter in a telecentric optical system. We demonstrate processing of microscopic images of unstained and stained histological sections of human thyroid tumor with improved contrast.

In-line phase-contrast breast tomosynthesis: a phantom feasibility study at a synchrotron radiation facility.

Abstract: The major objective is to adopt, apply and test developed in-house algorithms for volumetric breast reconstructions from projection images, obtained in in-line phase-contrast mode. Four angular sets, each consisting of 17 projection images obtained from four physical phantoms, were acquired at beamline ID17, European Synchroton Radiation Facility, Grenoble, France. The tomosynthesis arc was ±32°. The physical phantoms differed in complexity of texture and introduced features of interest. Three of the used phantoms were in-house developed, and made of epoxy resin, polymethyl-methacrylate and paraffin wax, while the fourth phantom was the CIRS BR3D. The projection images had a pixel size of 47 µm × 47 µm. Tomosynthesis images were reconstructed with standard shift-and-add (SAA) and filtered backprojection (FBP) algorithms. It was found that the edge enhancement observed in planar x-ray images is preserved in tomosynthesis images from both phantoms with homogeneous and highly heterogeneous backgrounds. In case of BR3D, it was found that features not visible in the planar case were well outlined in the tomosynthesis slices. In addition, the edge enhancement index calculated for features of interest was found to be much higher in tomosynthesis images reconstructed with FBP than in planar images and tomosynthesis images reconstructed with SAA. The comparison between images reconstructed by the two reconstruction algorithms shows an advantage for the FBP method in terms of better edge enhancement. Phase-contrast breast tomosynthesis realized in in-line mode benefits the detection of suspicious areas in mammography images by adding the edge enhancement effect to the reconstructed slices.

A versatile edge preserving image enhancement approach for medical images using guided filter

Abstract: Medical imaging systems often require image enhancement to visualize images of the human body and its organs. This would help medical professionals in irregularity or abnormality detection and diagnosis. This paper demonstrates a method to enhance medical related images. The proposed algorithm uses techniques, such as, guided filtering, edge enhancement, contrast stretching, and image fusion to enhance low resolution images. Visually, the proposed method produces better or comparable enhanced images than several state-of-the-art methods. In addition, we also test the performance of the proposed method with the method mentioned in [1].

Local filtration based scatter correction for cone-beam CT using primary modulation.

Abstract: Purpose Excessive scatter contamination fundamentally limits the image quality of cone-beam CT (CBCT), hindering its quantitative use in clinical applications. The author has previously proposed an effective scatter correction method for CBCT using primary modulation. A Fourier transform-based algorithm (FTPM) was implemented to estimate scatter from modulated projections, with a few limitations including the assumption of uniform modulation frequency and magnitude that becomes less accurate in the presence of beam-hardening and other nonideal effects. This paper aims to overcome the above drawbacks by developing a new algorithm for the primary modulation method with improved accuracy and reliability. Methods Incident x-ray intensities for each detector pixel with and without the interception of the modulator blocker are estimated from a modulated flat-field image. A new signal relationship is then developed to obtain a first scatter estimate from a modulated projection using a spatially varying modulation distribution. The method empirically adjusts the effective modulation magnitude for each projection ray to account for the beam-hardening effects. Estimated scatter signals with high expected errors are discarded in the generation of the final scatter distribution. The author proposes a technique of local filtration to accelerate major portions of the signal processing, and the new algorithm is referred to as local filtration based primary modulation (LFPM). Results The study on the Catphan® 600 phantom shows that LFPM effectively removes scatter-induced cupping artifacts on CBCT images and reduces the CT image error from 222 to 15 HU. In addition, the image contrast on eight contrast rods of the phantom is enhanced by a factor of 2 on average. On an anthropomorphic head phantom, LFPM reduces the CT image error from 153 to 18 HU and eliminates the streak artifacts observed on the result of FTPM with substantially improved image uniformity. On the Rando® phantom, LFPM reduces the CT image error from 278 to 4 HU around the object center. Conclusions As compared with the previously developed FTPM algorithm, LFPM enhances the imaging performance by using a more flexible data processing framework that does not require projection data downsampling or uniform modulation frequency and magnitude. It also becomes possible to discard suspicious scatter estimate values prior to the generation of a final scatter distribution and to model the beam-hardening effects on modulation for improved scatter estimation accuracy. The presented research further exploits the potential of the primary modulation method on scatter correction and facilitates its clinical adoption in CBCT imaging.

Preprocessing techniques of facial image with Median and Gabor filters

Abstract: Image Preprocessing is an essential factor for any Face image, when processing it for research purpose, The need for Preprocessing is due to its variation in Lightening condition, differences in Pose, Head orientation and Expressions because the quality of an Image depend on the effectiveness of capture device like CCTV, Webcams etc. The common Preprocessing involves Color Normalization, Noise Reduction, Edge Detection and Histogram Equalization. The aim of Preprocessing is to improve the quality of the Image and to enhance the Image features for further processing. In this paper Median filter is used for Color Normalization and Noise Reduction. Gabor filter is used for Edge enhancement and Histogram Equalization for Image contrast illumination. Hence an improved quality of Image is produced by using Hybrid filters this helps for the efficiency of producing result for any research processing.

Alternating guided image filtering

Abstract: Edge preserving filters aim to simplify the representation of images (e.g., by reducing noise or eliminating irrelevant detail) while preserving their most significant edges. These filters are typically nonlinear and locally smooth the image structure while minimizing both blurring and over-sharpening of visually important edges. Here we present the Alternating Guided Filter (AGF) that achieves edge preserving smoothing by combining two recently introduced filters: the Rolling Guided Filter (RGF) and the Smooth and iteratively Restore Filter (SiR). We show that the integration of RGF and SiR in an alternating iterative framework results in a new smoothing operator that preserves significant image edges while effectively eliminating small scale details. The AGF combines the large scale edge and local intensity preserving properties of the RGF with the edge restoring properties of the SiR while eliminating the drawbacks of both previous methods (i.e., edge curvature smoothing by RGF and local intensity reduction and restoration of small scale details near large scale edges by SiR). The AGF is simple to implement and efficient, and produces high-quality results. We demonstrate the effectiveness of AGF on a variety of images, and provide a public code to facilitate future studies. Subjects Algorithms and Analysis of Algorithms, Computer Vision

Cluster driven anisotropic diffusion for speckle reduction in ultrasound images

Abstract: In this paper, we propose a cluster-driven anisotropic diffusion (CDAD) filter for speckle reduction in ultrasound images. The proposed filter is based on the multiplicative noise model and is driven by K-means clustering algorithm. Instead of choosing homogeneous sample region with manual selection, the proposed algorithm is able to do it automatically (based on the clustering results). In addition, clustering result is used as a global characteristics descriptor to further improve the performance of noise removal as well as edge enhancement. The proposed filter was implemented and evaluated with real ultrasound images. Experimental results show that the proposed CDAD filter shows improved performance compared with Speckle Reducing Anisotropic Diffusion (SRAD).

Lane line confirmation method in lane line detection system

Abstract: The invention discloses a lane line confirmation method in a lane line detection system The method comprises the following steps that: 1, a camera collects an image; 2, edge enhancement is carried out on the image collected by the camera; 3, binary processing is carried out on the image after the edge enhancement; 4, candidate edge points at the inner side of a lane line are screened out according to characteristic rules of the lane line; 5, a fitting technology is adopted for carrying out fitting on the inner edge of the lane line, and obtaining a line or curve model of a lane; and 6, confirming the lane line The image collected by the camera in the step 1 is a gray level image or a color image, if the image is the color image, the color image is converted into the gray level image through a color image to gray level image conversion formula

Method and device for detecting multiple lane lines

Abstract: The invention discloses a method and device for detecting multiple lane lines, and belongs to the field of intelligent cars. The method comprises the steps: obtaining an image of a lane in front of a car through a camera device; converting the lane image into a gray scale image; carrying out the edge enhancement of a lane line region in the gray scale image, and obtaining an edge enhanced image; obtaining a gray scale segmentation threshold value, carrying out the binarization processing of the edge enhanced image according to the gray scale segmentation threshold value, and obtaining a binary image; judging the internal and external edge points of an internal lane line in the binary image; detecting and tracking the internal lane line according to the features of the lane line; detecting and tracking an external lane line in an external lane line detection region based on the internal lane line, wherein the external lane line detection region is a region from an internal left lane line to an internal right lane line. The method can improve the lane detection efficiency.

Spatial domain color image enhancement based on local processing

Abstract: In this paper, a color image enhancement based on local processing approach is proposed. The proposed algorithm includes image enhancement in spatial domain. Image is treated locally, means enhancement operator is applied only where it is needed. Proposed method takes place in three steps; initially luminance of image is enhanced by a non-linear transfer function. In second step, contrast enhancement is carried out using neighbourhood dependent approach and in the third step; tone reproduction is carried out by 2-D local Gamma correction. In this technique Hue and Saturation is preserved because the method is applied only on V (luminance) part of an HSV (Hue-Saturation-Luminance). Finally, Hue (H) and Saturation (S) component of the original image and enhanced Value component (V) are combined together and converted back to an RGB image. This algorithm is very effective for non-uniform illumination images. Performance of image enhancement is evaluated through visual perception, colorfulness index and number of saturated pixels (percentage). The experimental results validate that images improved by proposed algorithm are clearer, natural looking in comparison with other techniques of image enhancement.

PLIP based unsharp masking for medical image enhancement

Abstract: Medical image enhancement is an effective tool to improve visual quality of digital medical images. In this paper, we propose a new unsharp masking scheme for medical image enhancement. It embeds the PLIP multiplication into the unsharp masking framework. Experimental results demonstrate that the proposed method can effectively enhance the overall contrast and edges of medical images while suppressing background noise.

Improving iterative back projection super resolution model via anisotropic diffusion edge enhancement

Abstract: This improving technique based on combining an Iterative Back Projection (IBP) super resolution method with Anisotropic Diffusion (AD) technique for overcoming IBP weaknesses. The IBP has specialty to remove a reconstruction error and blurry effect iteratively manner in image registration place. However, it has a weakness from avoiding result image from chessboard effect and lost high frequency information. For this reason, this super resolution approach requires an edge enhancement technique to complement the weakness. Anisotropic diffusion is edge enhancement techniques and it has benefited to estimate a piecewise smooth image from a noisy input image. This paper proposed to integrate Anisotropic Diffusion techniques in IBP registration stages with an improvement in the IBP flow process model. This improvement in IBP model produced a result image in better appearing output with preserves high frequency information and less number of iteration process reconstruction.

Anisotropic edge enhancement in optical scanning holography with spiral phase filtering

Abstract: Anisotropic edge enhancement is simulated using a spiral phase plate (SPP) in optical scanning holography (OSH). We propose to use a delta function and an SPP as the pupil functions to realize anisotropic edge enhancement. The interference of these two pupils is used to two-dimensionally scan an object to record its edge-only information. This is done in three ways: first, by shifting the SPP, second, by using two offset SPPs of same charge, and finally, by using two oppositely charged SPPs. Our computer simulations show the capability of selectively enhancing the edges of a given object.

Modified unsharp masking detection using Otsu thresholding and Gray code

Abstract: In order to improve image quality, unsharp masking (USM) is a great solution for image enhancement. To detect USM sharpening, we propose an improved method called edge perpendicular Gray coding (EPGC). With EPGC, the number of feature points generated from binary encoding can be reduced to half and thus the execution of calculating histogram can be accelerated. In addition, we use Otsu thresholding to enhance Canny edge detection. As a result, the accuracy of USM detection is increased. Experimental results show that EPGC performs better than previous methods.

Enhancement of night movies using fuzzy representation of images

Abstract: A cheap personal camera is a perfect device that allows us to test algorithms for video enhancement. In this paper we present a cascade of filters based on a fuzzy representation of images. This representation tries to capture the uncertainty underlying in the intensity of a pixel by means of a fuzzy set. The cascade of filters is compared with the corresponding standard filters: blurring, sharpening and image averaging. Besides, experimentally we show that our approach provides similar results with a significant reduction of the computational time.

Multi region segmentation algorithm based on edge preserving for molten pool image

Abstract: This paper is aimed at the difficult problem of multi region segmentation of weld pool image, analyzed The difficulty of edge extraction in the inner region of the weld pool. According to the characteristics between pixel neighborhood space and neighbor pixel correlation, based on local standard deviation, presented a noise suppression, edge enhancement of the weld pool image multi region division and multi region edge detection algorithm, Through the test of the weld pool image, It shows that the algorithm can accurately divide the internal details of the weld pool. Finally, the Sobel operator, Roberts operator, Prewitt operator and the edge detection results of the weld pool image are analyzed and compared by experiments, The results show that the algorithm in this paper is much better than other algorithms, At last, the accuracy of the algorithm is tested by the difference shadow detection, a continuous multi region edge was obtained by the expansion of corrosion.

Device to seamlessly merge the images into a single composition with automatic contrast adjustment and gradients

Abstract: FIELD: measuring equipmentSUBSTANCE: device seamless merging images comprises two boot block image clock, two search block control points search unit pixels association calculation unit matrices transform the two blocks of the matrix transformation unit zero padding block to the edge enhancement unit for calculating a curve, three unit masking unit finding masks block allocation pool area, finding the boundary of the block association, block the removal of areas, adjust the contrast of the two blocks, two blocks combiner applying the gradient image output unit resultsEFFECT: obtaining a combined image with smooth border crossing1 cl, 2 dwg

Nonlinear Optical Spatial Filtering for Medical Image Processing

Abstract: The nonlinear properties of Tris(acetylacetonato) Manganese(III) are used to manipulate the spatial frequencies at the Fourier plane using 4f-z scan. The technique is a simple self-adaptive all-optical system, which performs image processing and nonlinear optical measurements at the same time. Preferred spatial frequencies can be selected by shifting the nonlinear sample through the focus. Edge enhancement was demonstrated by filtering of low frequency with the nonlinear material at the Fourier plane.