• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.9-16
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• 2008

Recently, there are a lot of multimedia products using image interpolation system. However, most interpolation systems in existence suffer visually to some extents from the effects of blurred edges and jagged artifacts in the image. In this paper, we propose a new adaptive linear interpolation system that uses the sub-pixel. The proposed system calculate the warped distance among the pixels of an image by optimizing length parameter. A new cost function is introduced to reflect frequency properties of the origin data in order to improve image quality. Experimental results show that our new algorithm significantly outperforms conventional interpolation methods in subjective quality, and in most cases, in terms of PSNR as well.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.238-246
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• 2005

This paper proposes an iterative high-resolution image interpolation algorithm using spatially adaptive constraints and regularization functional. The proposed algorithm adapts adaptive constraints according to the direction of..edges in an image, and can restore high-resolution image by optimizing regularization functional at each iteration, which is suitable for edge directional regularization. The proposed algorithm outperforms the conventional adaptive interpolation methods as well as non-adaptive ones, which not only can restore high frequency components, but also effectively reduce undesirable effects such as noise. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.856-873
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• 2011

Reversible watermarking is an open problem in information hiding field, with embedding the encoded bit '1' or '0' into some sensitive images, such as the law enforcement, medical records and military images. The technique can retrieve the original image without distortion, after the embedded message has been extracted. Histogram-based scheme is a remarkable breakthrough in reversible watermarking schemes, in terms of high embedding capacity and low distortion. This scheme is lack of capacity control due to the requirement for embedding large-scale data, because the largest hidden capacity is decided by the amount of pixels with the peak point. In this paper, we propose a reversible watermarking scheme to enlarge the number of pixels with the peak point as large as possible. This algorithm is based on an adaptive edge-guided interpolation, furthermore, hides messages by interpolation-error, i.e. the difference between the original and interpolated image value. Simulation results compared with other state-of-the-art reversible watermarking schemes in this paper demonstrate the validity of the proposed algorithm.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.51-58
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• 2010

This paper proposes an edge adaptive color interpolation for an ultra-small HD-grade complementary metal-oxide semiconductor (CMOS) video sensor in camera phones that can process 720-p/30-fps videos. Recently, proposed methods with great image quality perceptually reconstruct the green component and then estimate the red/blue component using the reconstructed green and neighbor red and blue pixels. However, these methods require the bulky memory line buffers in order to temporally store the reconstructed green components. The edge adaptive color interpolation method uses seven or nine patterns to calculate the six edge directions. At the same time, the threshold values are adaptively adjusted by the sum of the color values of the selected pixels. This method selects the suitable one among the patterns using two flowcharts proposed in this paper, and then interpolates the missing color values. For verification, we calculated the peak-signal-to-noise-ratio (PSNR) in the test images, which were processed by the proposed algorithm, and compared the calculated PSNR of the existing methods. The proposed color interpolation is also fabricated with the 0.18-${\mu}m$ CMOS flash memory process.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.501-509
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• 2011

In this paper, we propose an edge profile adaptive bi-directional diffusion interpolation method which consists of shock filter and level set. In recent years many interpolation methods have been proposed but all methods have some degrees of artifacts such as blurring and jaggies. To solve these problems, we adaptively apply shock filter and level set method where shock filter enhances edge along the normal direction and level set method removes jaggies artifact along the tangent direction. After the initial interpolation, weights of shock filter and level set are locally adjusted according to the edge profile. By adaptive coupling shock filter with level set method, the proposed method can remove jaggies artifact and enhance the edge. Experimental results show that the average PSNR and MSSIM of our method are increased, and contour smoothness and edge sharpness are also improved.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.54-57
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• 2000

In this paper, we propose a new interpolation method by using the motion between two moving image frames. In the proposed method, the movement is detected by using neighborhood pixels of target pixel in the past frame and the present frame. Then, H-shaped pseudomedian filter (below HPMED) is used for the still part of the image and Delta-shaped interpolation filter (below $\Delta$-shaped) for used in the moving part of the image. We detect the movement by comparing the differences between pixels in 4${\times}$5 window of the past frame and the present frame; the difference has a critical value. We simultaneously accomplish checking PSNR(peak signal noise ratio) and subjective assessment that is placed the focus on edge characteristic for assessment of result in computer simulation. The results show that the proposed adaptive method is better than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1000-1009
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• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.240-248
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• 2013

In this paper, we propose a super-resolution algorithm using an adaptive weighted interpolation(AWI) and discrete wavelet transform(DWT). In general, super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm is increased and it causes the increase of processing time. In the proposed algorithm, we first find high-frequency sub-bands by using DWT. Then we apply an AWI to the obtained high-frequency sub-bands to make them have the same size as the input image. Now, the interpolated high-frequency sub-bands and input image are properly combined and perform the inverse DWT. For the experiments, we use the down-sampled version of the original image($512{\times}512$) as a test image($256{\times}256$). Through experiment, we confirm the improved efficiency of the proposed algorithm comparing with interpolation algorithms and also save the processing time comparing with the probability based algorithms even with the similar performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6017-6037
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• 2017

In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1204-1209
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• 2008

Design is important in the IT, digital appliance, and auto industries. Aesthetic and art images are being applied for better design satisfaction of the products. Various artistic image patterns are used to satisfy demand of design, but it takes much lead-time and effort to implement them for making dies and molds. In this paper, a hybrid reverse engineering method generating accurate 3D engraving models from 2D art images is proposed through image processing, 3D reconstruction, and NURBS interpolation methods. In order to generate the 3D model from the 2D artistic image, cloud points with z-depth are extracted according to intensity values of the image. An adaptive median filter and harmonic filter are used to obtain the intensity values accurately. NURBS surfaces are generated through the interpolation of the cloud points. Performance of the developed system is to be confirmed through the realization of Mona Lisa and Golden Gate Bridge.