• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.14-22
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• 2001

The frequency responses on the sub-pixel evaluation technique were investigated using the Monte-calro Simulation technique. The frequency response by the FFT based cross-correlation gives very good results, however, the gain loss does exist for the small displacement, (less than 0.5 pixel). While, the no gain loss is observed in the Direct Cross-correlation, however, the sub-pixel accuracy was limited to be about 0.1 pixel, i.e., it could not detect the small displacement. To detect the higher accurate sub-pixel displacement, the gradient based technique is the best. For the small interrogation area (e.g., 4x4), only the gradient technique can detect the small displacement correctly.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.120-127
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• 2010

This paper presents a SR method using adaptive interpolation based on local gradient features to obtain a high quality SR image. In this method, the distance between the interpolated pixel and the neighboring valid pixel is considered by using local gradient properties. The interpolation coefficients take the local gradient of the LR images into account. The smaller the local gradient of a pixel is, the more influence it should have on the interpolated pixel. And the median filter is finally applied to reduce the blurring and noise of the interpolated HR image. Experiment results show the effectiveness of the proposed method in comparison with other methods, especially in the edge areas of the images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.391-397
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• 2003

This paper is about the digital image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.95-99
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• 2018

In this paper, we propose an efficient pixel value prediction algorithm that can accurately predict pixel value using neighboring pixel values scanned in reverse s-order in the image. Generally, image has similarity with similar values between adjacent pixel values, and may have directional edge characteristics. In this paper, we proposed a method to improve pixel value prediction accuracy by improving GAP(Gradient Adjacent Pixel) algorithm for predicting pixel value by using similarity between adjacent pixels and edge characteristics. The proposed method increases the accuracy of the predicted pixel value by precisely predicting the pixel value using the positional weights of the neighboring pixels. Experiments on real images confirmed the superiority of the proposed algorithm. The proposed algorithm is useful for applications such as reversible data hiding, reversible watermarking, and data compression applications.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.49-60
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• 2020

To solve the edge ringing or block effect caused by the partial differential diffusion in image enhancement domain, a new image enhancement algorithm based on bidirectional diffusion, which smooths the flat region or isolated noise region and sharpens the edge region in different types of defect images on aviation composites, is presented. Taking the image pixel's neighborhood intensity and spatial characteristics as the attribute descriptor, the presented bidirectional diffusion model adaptively chooses different diffusion criteria in different defect image regions, which are elaborated are as follows. The forward diffusion is adopted to denoise along the pixel's gradient direction and edge direction in the pixel's smoothing area while the backward diffusion is used to sharpen along the pixel's gradient direction and the forward diffusion is used to smooth along the pixel's edge direction in the pixel's edge region. The comparison experiments were implemented in the delamination, inclusion, channel, shrinkage, blowhole and crack defect images, and the comparison results indicate that our algorithm not only preserves the image feature better but also improves the image contrast more obviously.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.113-117
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• 2007

In this paper, we propose a new method for determining automatically the size of the matching window using histogram of the gradient in order to improve the performance of stereo matching using one-meter resolution satellite imagery. For each pixel, we generate Flatness Index Image by calculating the mean value of the vertical or horizontal intensity gradients of the 4-neighbors of every pixel in the entire image. The edge pixel has high flatness index value, while the non-edge pixel has low flatness index value. By using the histogram of the Flatness Index Image, we find a flatness threshold value to determine whether a pixel is edge pixel or non-edge pixel. If a pixel has higher flatness index value than the flatness threshold value, we classify the pixel into edge pixel, otherwise we classify the pixel into non-edge pixel. If the ratio of the number of non-edge pixels in initial matching window is low, then we consider the pixel to be in homogeneous region and enlarge the size of the matching window We repeat this process until the size of matching window reaches to a maximum size. In the experiment, we used IKONOS satellite stereo imagery and obtained more improved matching results than the matching method using fixed matching window size.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.17-26
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• 2008

This paper has for its object to propose AFOD(Adaptive First-Order Decimator) which sets a value of decimated element as an average of a value of neighbor intelligible component and a output value of FOD(First-Order Decimator) for the target pixel, and to analyze its performance in terms of subjective image quality and hardware complexity. In the proposed AFOD, a target pixel located at the center of sliding window is selected first, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible component is defined by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. Since the proposed method adaptively reflects neighbor intelligible informations of neighbor pixels on the decimated element according to each local intelligible weight, it can effectively suppress the blurring effect being the demerit of FOD. It also possesses the advantages that it can keep the merits of FOD with the good results on average but also lower computational cost.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.46-52
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• 2016

We propose a new type of semi-global matching (SGM) in order to solve a streaking problem arising from conventional SGM. Conventional SGM imposes a penalty to a pixel when the disparity of the pixel differs from that of the previous pixel along a scan path, and thus, disparity changes are not easily allowed, causing the streaking effect. The road surface is an appropriate target for such an effect, because the colors of the surfaces are very similar, and the image pixels corresponding to the surfaces show disparities that change very smoothly along the viewing direction. In contrast to conventional SGM, the new type of SGM imposes penalties depending on the disparity gradients, and thus, the streaking effect is controlled. The experimental results show the effectiveness of the proposed SGM method.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.