Showing papers on "Edge enhancement published in 2017"

Contrast Limited Adaptive Histogram Equalization Based Fusion for Underwater Image Enhancement

Abstract: In order to improve contrast and restore color for underwater image captured by camera sensors without suffering from insufficient details and color cast, a fusion algorithm for image enhancement in different color spaces based on contrast limited adaptive histogram equalization (CLAHE) is proposed in this article. The original color image is first converted from RGB color space to two different special color spaces: YIQ and HSI. The color space conversion from RGB to YIQ is a linear transformation, while the RGB to HSI conversion is nonlinear. Then, the algorithm separately operates CLAHE in YIQ and HSI color spaces to obtain two different enhancement images. The luminance component (Y) in the YIQ color space and the intensity component (I) in the HSI color space are enhanced with CLAHE algorithm. The CLAHE has two key parameters: Block Size and Clip Limit, which mainly control the quality of CLAHE enhancement image. After that, the YIQ and HSI enhancement images are respectively converted backward to RGB color. When the three components of red, green, and blue are not coherent in the YIQ-RGB or HSI-RGB images, the three components will have to be harmonized with the CLAHE algorithm in RGB space. Finally, with 4 direction Sobel edge detector in the bounded general logarithm ratio operation, a self-adaptive weight selection nonlinear image enhancement is carried out to fuse YIQ-RGB and HSI-RGB images together to achieve the final fused image. The enhancement fusion algorithm has two key factors: average of Sobel edge detector and fusion coefficient, and these two factors determine the effects of enhancement fusion algorithm. A series of evaluate metrics such as mean, contrast, entropy, colorfulness metric (CM), mean square error (MSE) and peak signal to noise ratio (PSNR) are used to assess the proposed enhancement algorithm. The experiments results showed that the proposed algorithm provides more detail enhancement and higher values of colorfulness restoration as compared to other existing image enhancement algorithms. The proposed algorithm can suppress effectively noise interference, improve the image quality for underwater image availably.

Polarization-based spatial filtering for directional and nondirectional edge enhancement using an S-waveplate

Abstract: Using polarization as an additional parameter apart from amplitude and phase in spatial filtering experiments offers additional advantages and possibilities. An S-waveplate that can convert a linearly polarized light into radially or azimuthally polarized light can also be used for isotropic edge enhancement. For anisotropic edge enhancement, introduction of a polarizer at the output was recommended and edge selection was done by orientation of the polarizer. But the full potential of the S-waveplate as a spatial filter has not been exploited so far. Unlike the standard amplitude and phase-based Fourier filters, which are independent to the state of polarization of the illuminating beam, the S-waveplate acts in a different way depending on the state of polarization. The edge selection does not need to be carried out by changing the orientation of the polarizer. With a fixed polarizer at the output, we show that either isotropic or anisotropic edge enhancement in any desired orientation can be performed by operating the same spatial filter setup in different illuminating polarization states.

A Study on Different Edge Detection Techniques in Digital Image Processing

Abstract: Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

An Image Contrast Enhancement Algorithm Using PLIP-Based Histogram Modification

Abstract: Contrast enhancement is an important tool for producing informative and visually pleasing images. However,conventional image contrast enhancement methods often sufferfrom the drawback of excessive enhancement. In this paper we propose a new image contrast enhancement algorithm. It embedsPLIP operations into a robust histogram modification framework.Experimental results demonstrate that the proposed algorithm can effectively enhance image contrast while preventing excessive enhancement.

Image Processing With Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

Abstract: Hardware-based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a 2-D periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks, such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost.

Detections of sustainable areas for steganographic embedding

Abstract: An approach to address the shortcomings of existing steganographic systems is considered. The mechanism of detection of sustainable image areas on the basis of the method the edge enhancement image objects is offered. A comparative evaluation of the experimental results to identify areas for sustainable steganographic embedding is carrying out.

A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform domain

Abstract: The intelligibility of an image can be influenced by the pseudo-Gibbs phenomenon, a small dynamic range, low-contrast, blurred edge and noise pollution that occurs in the process of image enhanceme...

An improved fast level set method initialized with a combination of k-means clustering and Otsu thresholding for unsupervised change detection from SAR images

Abstract: Detection of changes in synthetic aperture radar (SAR) images is an important challenge due to the effects of speckle noise on these images. In recent years, appropriate methods for SAR-based-change detection have been developed based on the level set methods (LSM). These methods need to set parameters for defining a proper initial contour. Moreover, the gradient information is only employed in the total energy of these methods for segmentation of the difference image. In this study, a novel method has been proposed for unsupervised change detection of multitemporal SAR images based on the improved fast level set method (IFLSM) initialized with a combination of k-means and Otsu techniques. The proposed method utilizes the discrete wavelet transform (DWT) fusion strategy and edge enhancement to achieve a noise-resistant difference image from the mean-ratio and log-ratio images. Afterward, the generated binary change map (CM) by applying a combination of k-means and Otsu techniques on the difference image is used as the initial contour to achieve a final CM on difference image using the IFLSM. To check advantages of the proposed method, experiments are applied on two sets of multitemporal SAR images corresponding to artificial Chitgar Lake (under reconstruction) in Tehran (Iran) taken by TerraSAR-X satellite in 2011 and 2012, and corresponding to San Pablo and Briones reservoirs in California (USA) acquired by ERS-2 satellite in 2003 and 2004. Results of proposed method were compared with results of some well-known unsupervised change detection methods. Experimental results prove the sufficiency of the proposed method in unsupervised change detection in terms of accuracy, implementation time, and computational complexity.

Anisotropic edge enhancement with spiral zone plate under femtosecond laser illumination.

Abstract: Fractional and de-centered phase spiral zone plates (SZPs) are proposed for anisotropic edge enhancement using a femtosecond laser. The transmission functions of the two types of phase SZPs are deduced and the diffraction distributions are theoretically analyzed and simulated as well. By setting the fractional topological charge p and the orientation angle ϑ of a fractional SZP (FSZP), the intensity and the direction of the anisotropic edge enhancement can be controlled. A de-centered SZP (DSZP) can be obtained by shifting the coordinates of the traditional phase SZP while the topological charge equals to 1. The intensity and direction of the anisotropic edge enhancement can be controlled by setting the displacement distance r0 and the azimuthal angle φ0 of a DSZP. The anisotropic edge enhancement of the two phase SZPs was experimentally demonstrated with a phase pattern and living biological cells under femtosecond laser illumination.

Image enhancement method

Abstract: The present invention relates to the image processing field, more specifically, to an image enhancement method The concrete steps comprises: a) performing the de-noising processing of an input image to obtain a de-noising image; b) performing edge extraction of the de-noising image to obtain an edge image; c) performing image enhancement processing of the edge image to obtain the de-noising and edge enhancement image; d) employing the histogram equalization method with controllable brightness to perform processing of the de-noising image to obtain a global enhancement image; and e) performing linear superposition of the obtained image through the step c and the step d, and obtaining a final output image Through combination of the histogram equalization method with controllable brightness and the UM (Unsharp Masking) algorithm idea, the image enhancement method can realize that the output brightness can be automatically regulated with the user requirement, and can obtain a global enhanced output image with obviously improved contrast through setting an appropriate brightness value so as to reach the purpose of the image enhancement

Image enhancement with the application of local and global enhancement methods for dark images

Abstract: Image enhancement is a technique used to get a better quality of an image in terms of its clarity, brightness and to give the human eye comfortable to look at. There are different types of techniques to give good quality of an image. Global image contrast enhancement is one of the most commonly used technique to enhance the quality of an image, but it has some disadvantages with the fact that it does not consider the local details of an image. Local details of an image are very important while analyzing an image, which is that of the scientific study of an image like the image taken from planetary bodies, satellite image and medical images. Local details of an image are very important for diagnosing a particular ailment. When either local contrast enhancement or global contrast enhancement is used alone, there is loss of brightness of the image. In order to address and reduce this discrepancy of individual enhancement methods, a new method is presented in this paper, that uses both local and global enhancement methods on the same image. First, the image is locally enhanced and the output is again processed by the global enhancement method thereby giving a properly enhanced image without losing the brightness of the image. This enhancement method is simulated in MATLAB and results are verified on the parameters of image quality.

Remote sensing image enhancement via bilateral filtering

Abstract: Remote sensing image enhancement methods have to increase the contrast and emphasize the edges, while preserving the color. In this study, an enhancement method based on bilateral filtering is proposed. We propose to extract the details of the image by a multiscale bilateral filter and add these details to the original image using a weighting scheme. Visual results and evaluation metrics show that the proposed method, enhance the image better than the former methods while it better preserves the original color information.

Speckle-tracking X-ray phase-contrast imaging for samples with obvious edge-enhancement effect

Abstract: Compared to the grating or crystal-based X-ray phase contrast imaging, the speckle-tracking method has the advantages of a simple setup and two-dimensional imaging. However, the edge-enhancement effect prevents the application of the speckle-tracking imaging to a large variety of samples. In this letter, an image reconstruction method is proposed to solve this problem. The experimental results from phantom, a biomedical sample, and a sample with a speckle-resembling structure demonstrated that the proposed method is efficacious in eliminating the effect of edge enhancement. The proposed method may greatly expand the application of the speckle-tracking method to most biomedical and material samples.

Compact OAM microscope for edge enhancement of biomedical and object samples

Abstract: The production of orbital angular momentum (OAM) by using a q-plate, which functions as an electrically tunable spatial frequency filter, provides a simple and efficient method of edge contrast in biological and medical sample imaging for histological evaluation of tissue, smears, and PAP smears. An instrument producing OAM, such as a q-plate, situated at the Fourier plane of a 4f lens system, similar to the use of a high-pass spatial filter, allows the passage of high spatial frequencies and enables the production of an image with highly illuminated edges contrasted against a dark background for both opaque and transparent objects. Compared with ordinary spiral phase plates and spatial light modulators, the q-plate has the added advantage of electric control and tunability.

Quantitative investigation of the edge enhancement in in-line phase contrast projections and tomosynthesis provided by distributing microbubbles on the interface between two tissues: A phantom study

Abstract: The objective of this study was to quantitatively investigate the ability to distribute microbubbles along the interface between two tissues, in an effort to improve the edge and/or boundary features in phase contrast imaging. The experiments were conducted by employing a custom designed tissue simulating phantom, which also simulated a clinical condition where the ligand-targeted microbubbles are self-aggregated on the endothelium of blood vessels surrounding malignant cells. Four different concentrations of microbubble suspensions were injected into the phantom: 0%, 0.1%, 0.2%, and 0.4%. A time delay of 5 min was implemented before image acquisition to allow the microbubbles to become distributed at the interface between the acrylic and the cavity simulating a blood vessel segment. For comparison purposes, images were acquired using three system configurations for both projection and tomosynthesis imaging with a fixed radiation dose delivery: conventional low-energy contact mode, low-energy in-line phase contrast and high-energy in-line phase contrast. The resultant images illustrate the edge feature enhancements in the in-line phase contrast imaging mode when the microbubble concentration is extremely low. The quantitative edge-enhancement-to-noise ratio calculations not only agree with the direct image observations, but also indicate that the edge feature enhancement can be improved by increasing the microbubble concentration. In addition, high-energy in-line phase contrast imaging provided better performance in detecting low-concentration microbubble distributions.

Diffraction imaging enhancement using spectral decomposition for faults, fracture zones, and collapse feature detection in a Middle East carbonate field

Abstract: Diffraction imaging is demonstrated in this case study to improve horizontal resolution over conventional reflection imaging. Edge enhancement, using spectral decomposition on diffraction imaged data, further enhances the capabilities of detecting faults, fracture zones, and collapse features improving the spatial resolution and edge detection for higher resolution seismic interpretation. Spectral decomposition also provides an effective tool for separating low-frequency reflection data noise from diffraction imaged data, improving the interpretability of the diffraction imaged data. This case study also demonstrates that edge enhancement using spectral decomposition improves the ability of spatially correlating the edges of collapse features, detected with diffraction imaged data, to drilling mud losses in carbonates. Detecting overburden collapse features with diffraction imaging could provide economic benefits, avoiding encounters with high perm zones, preventing mud loss expenses and increased drilling time, from days to weeks, and controlling the well.

An image enhancement technique using nonlinear transfer function and unsharp masking in multispectral endoscope

Abstract: This paper studies the realization of image processing algorithm of multispectral endoscope. The research contents include: local brightness enhancement and adaptive contrast enhancement. Firstly, this paper transforms the image from the RGB space to the HSV space, and then carries on the image enhancement processing to the V space, finally transforms to the RGB space. Local brightness enhancement algorithm divides V space image into smaller windows, and then calculates the nonlinear transfer function of each window, which enhances the pixels in the window, and finally the contrast of brightness enhanced image is restored. The adaptive contrast enhancement adopts the unsharp mask technique based on the guided filter. First of all, this paper uses guided filter to the RGB channel of the original image and gets the unsharp mask of each channel, then plus a scaled image which is the result of the original image subtracts the unsharp mask. So the enhancement of the image is achieved. This paper uses subjective evaluation criteria and enhance factor α to evaluate the effect of enhancement. And this paper compares the enhancement effect of the proposed image enhancement algorithm and the traditional algorithm. The results show that the α of histogram equalization is smallest and AINDANE method is better than histogram equalization. The proposed method has the best α. The subjective evaluation also shows that the effect of HE is not satisfactory and the proposed method enhances the detail information tremendously. The subjective and objective criteria shows that the proposed method produces better enhancement effect.

Image pickup apparatus and image processing method

Abstract: An image pickup apparatus includes an image pickup device including a plurality of pixels arrayed at a predetermined pixel pitch, a shift mechanism configured to perform a pixel shift in a movement amount which is a non-integral multiple of the pixel pitch, a microcomputer configured to cause the image pickup device to pick up an image at pixel shifting positions to respectively acquire a plurality of pieces of image data, a synthesis processing section configured to synthesize the acquired plurality of pieces of image data to generate composite image data with a high resolution, and an image processing section configured to determine an edge enhancement parameter based on a characteristic relating to a pixel opening of the composite image data and perform edge enhancement processing for the composite image data.

Edge enhancement of liver CT images using non subsampled shearlet transform based multislice fusion

Abstract: Segmentation of liver from the computed tomogram (CT) images of the abdomen is a challenging task as the liver boundaries are weak in nature. Multi slice fusion of abdominal CT images based on Non Subsampled Shearlet Transform (NSST) is proposed as an edge enhancement technique. Prior to liver segmentation, two adjacent slices of liver CT images are decomposed by means of NSST in different scales and in different directions to obtain low and high frequency sub band coefficients. The information contents of the low and high frequency sub bands are fused using fusion rules based on phase congruency and directive contrast respectively. To achieve better segmentation accuracy, Sum Modified Laplacian (SML) is integrated with the contrast features measure for effective fusion of edge information. Finally the edge enhanced image is obtained using NSST reconstruction. The effectiveness of the proposed edge enhancement technique is quantified by performing segmentation with and without fusion process. From the acquired results, it is obvious that the proposed fusion framework capture the edge detail information of the source images very effectively and can provide better edge information than the one obtained through individual images, thereby achieving improvement in segmentation accuracy by 60.11%.

Image processing method and apparatus

Abstract: The invention discloses an image processing method and apparatus. An image comprises n image blocks. The method comprises the steps of judging whether an input image block is an edge of the image or not; when the image block is determined to be the edge of the image, performing edge enhancement processing on the image block to obtain edge enhancement intensity information of the image block; according to a preset mapping relationship between the edge enhancement intensity information and color suppression intensity, judging an interval, where the edge enhancement intensity information is located, in the preset mapping relationship between the edge enhancement intensity information and the color suppression intensity; according to the interval, selecting the color suppression intensity of the image block; and performing color suppression processing on the chromaticity of the image block by using the color suppression intensity, thereby obtaining a chromaticity value of the image block subjected to the color suppression processing. By adopting the scheme, the image quality can be improved while the calculation amount of image processing is reduced, and the cost is reduced.

Photo-id of blue whale by means of the dorsal fin using clustering algorithms and color local complexity estimation for mobile devices

Abstract: We present an automatic program of blue whale photo-identification for mobile devices. The proposed technique works in the wavelet domain to reduce the image size and the processing time of the proposed algorithm, and with an edge enhancement filter, the characteristics of the blue whale are preserved. Additionally, an image palette reduction algorithm based on local image complexity estimation is introduced to eliminate redundant colors, thus decreasing the number of pixels that are bad classified in the segmentation process and minimizing the resource consumption of the mobile device. The segmented image is obtained with the FCM (fuzzy C-means) or K-means algorithms incorporating a dynamic filtering which is proposed in this paper to improve the brightness and contrast of the acquired image increasing the performance of the image segmentation. Experimental results show that the proposed approach potentially could provide a real-time solution to photo-id of blue whale images and it can be transportable and portable power for mobile devices. Finally, the proposed methodology is simple, efficient, and feasible for photo-id applications in mobile devices.

Readability Enhancement of Low Light Videos Based on Discrete Wavelet Transform

Abstract: In this paper, we propose readability enhancement of low light videos based on discrete wavelet transform (DWT). Captured videos under the low light condition have a narrow dynamic range (low contrast) with a dark tone as well as are highly corrupted by noise. We achieve both contrast enhancement and noise reduction in low light videos using wavelet coefficients. First, we perform normalization to stretch a dynamic range of an image. Then, we decompose the image into high-pass and low-pass sub-bands using DWT. Next, we perform de-noising and weak edge enhancement in the high-pass sub-bands (LH, HL, HH) and contrast enhancement in the low-pass sub-band (LL). Finally, we conduct color correction to compensate for color distortions caused by contrast enhancement. Experimental results demonstrate that the proposed method outperforms state-of-the-art ones in contrast enhancement, noise reduction, and color reproduction in terms of both subjective and objective evaluations.

A Novel PDE-Based Single Image Super-Resolution Reconstruction Method

Abstract: For applications such as remote sensing imaging and medical imaging, high-resolution (HR) images are urgently required. Image Super-Resolution (SR) reconstruction has great application prospects in optical imaging. In this paper, we propose a novel unified Partial Differential Equation (PDE)-based method to single image SR reconstruction. Firstly, two directional diffusion terms calculated by Anisotropic Nonlinear Structure Tensor (ANLST) are constructed, combing information of all channels to prevent singular results, making full use of its directional diffusion feature. Secondly, by introducing multiple orientations estimation using high order matrix-valued tensor instead of gradient, orientations can be estimated more precisely for junctions or corners. As a unique descriptor of orientations, mixed orientation parameter (MOP) is separated into two orientations by finding roots of a second-order polynomial in the nonlinear part. Then, we synthesize a Gradient Vector Flow (GVF) shock filter to balance edge enhancement and de-noising process. Experimental results confirm the validity of the method and show that the method enhances image edges, restores corners or junctions, and suppresses noise robustness, which is competitive with the existing methods.

Perceptual contrast enhancement in visual rendering of astrophotographs

Abstract: Abstract. When we perform a visual analysis of a cosmic object photograph, the contrast plays a fundamental role. We present an approach based on spatial color algorithms to enhance local contrast to make it easier to detect relevant information. We show very promising results on amateur photographs of deep sky objects. The results are presented for a qualitative and subjective visual evaluation and for a quantitative evaluation through image quality measures.

Ultrasonic image processing method and system

Abstract: The application discloses an ultrasonic image processing method and system. The ultrasonic image processing method comprises the following steps: original ultrasonic image data is obtained and subjected to filtering and noise reduction operation, and a filtered de-noised image can be obtained; the de-noised image is subjected to edge enhancement operation, an edge enhancement image can be obtained after edge enhancement operation, texture blending operation is performed on the edge enhancement image and the original ultrasonic image data, and a final ultrasonic image can be obtained. Via the ultrasonic image processing method and system, no image segmentation is needed during image processing procedures, edge enhancement and spot suppression of ultrasonic images can be realized, and image processing efficiency can also be improved.