• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.215-216
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• 2007

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3397-3413
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• 2016

Considering that the layered cellular automata (LCA) are naturally fit for representing image data in various applications, a novel reverse iterative image encryption scheme based on LCA is proposed. Specifically, the plain image is set as the final configuration of an 8-layer CA, and some sequences derived from a random sequence are set as the pre-final configuration, which ensure that the same plain image will never be encrypted in the same way when encrypted many times. Then, this LCA is backward evolved by following some reversible two order rules, which are generated with the aid of a newly defined T-shaped neighborhood. The cipher image is obtained from the recovered initial configuration. Several analyses and experimental results show that the proposed scheme possesses a high security level and executive performance.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.643-649
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• 2016

This paper presents a new image cache algorithm for real-time implementation of high-resolution color image warping. The cache memory is divided into four cache memory modules for simultaneous readout of four input image pixels in consideration of the color filter array (CFA) pattern of an image sensor and CFA image warping. In addition, a pipeline structure from the cache memory to an interpolator is shown to guarantee the generation of an output image pixel at each system clock cycle. The proposed image cache algorithm is applied to an FPGA-based real-time color image warping, and experimental results are presented to show the validity of the proposed method.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• Current Optics and Photonics
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• v.5 no.6
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• pp.686-698
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• 2021

A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.311-312
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• 2006

In this paper, a real-time stereoscopic image conversion method using a single frame from a 2-D image is proposed. If original image is too much dark, it is difficult to create correct luminance value. So stereoscopic image is generated after applied image enhancement algorithm to original image. The Stereoscopic image is generated by creating depth map using vertical position information and parallax processing.

• Progress in Medical Physics
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• v.20 no.4
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• pp.199-207
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• 2009

It is important to initialize Image Plate (IP) completely for removing residual latent image by sodium lamp for reliability and repeatability of computed radiography (CR) system. The purpose of this study was to evaluate latent images of computed radiography (CR) images respect to delay time after erasure of foregone latent image and its effect, and erasure level. Erasure thoroughness for CR acceptance test from American Association of Physicist in Medicine (AAPM) Report 93 (2006) was also evaluated. Measurements were made on a CR (Agfa CR 25; Agfa, BELGIUM) system. Chest postero-anterior (PA), Hand PA, L-spine lateral radiographs were chosen for evaluation. Chest phantom (3D-torso; CIRS, USA) was used for Chest PA and L-spine lateral radiography. For Hand PA radiography, projections was done without phantom. Except Hand PA radiographs, noise was increased with delay time, and ghost image was appeared on overexposed area. Effect of delay after erasure on latent image was not seen on naked eye, but standard deviation (SD) of pixel value on overexposed area was relatively higher than that of other areas. On Hand PA and Chest PA radiographs, noise were not occurred by adjustment of erasure level. On L-spine lateral images at lower erasure level than standard level, noise including ghost image were occurred because of high tube current. Erasure thoroughness of CR system in our department was to be proved by these evaluation. The results of this study could be used as a baseline for IP initialization and reliability of CR images.

• Current Optics and Photonics
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• v.8 no.3
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• Journal of Information Display
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• v.8 no.3
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• pp.29-33
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• 2007

The temporal dark image sticking phenomena are examined and compared for the two different electrode structures such as the face-to-face and coplanar sustain electrode structure. To compare the temporal dark image sticking phenomena for both structures, the differences in the infrared emission profile, luminance, and perceived luminance of the image sticking cells and the non image sticking cells were measured. It is observed that the temporal dark image sticking is mitigated for the face-to-face structure. The mitigation of the temporal dark image sticking for the face-to-face structure is due to the slight increase in the panel temperature induced by the ITO-less electrode structure.