• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.240-252
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• 2023

Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.1
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• pp.78-89
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• 1999

Clothes enhance visual images through the interaction between space and background of the wearer. The influence of background is important as that of the clothes when the observer understands the images. We look at fashion pictures used as important as that various backgrounds are presented depending on the image of the clothes. The clothing the model wears in the pictures takes on shape and space which supports the clothes. The background interact to from the whole image. The background has an important influence on the delivery of image for the clothes. However when the clothes are presented in the background there are some cases that all or parts of clothes can be shown. We must consider the composition ratio of the clothes and background which influences the whole image of the clothing. These interactions and influences on the whole image in regards to clothing background and the ratio will be the focus of this study. clothing was Modern Mannish Casual, Feminine, Ground was decided artificial setting 1 natural setting 1, indoor setting 1, artificial setting 2, natural setting 2, indoor setting 2, Percentage of Clothing was 80% , 140%, 200%,. Thus visual stimulus were 72 pictures that were combined Clothing Ground and Percentage of Clothing, the main survey of questionary consisted of their evaluation of the Picture image combined Clothing and Ground by 30 semantic differential bi-polar scales and the subjects were 50 students majoring in clothing and textile. The data analyzed by factor analysis MCA, MDS, The major finding were as follows : 1) As a result of factor analysis, 5 factors -Attractiveness Hardness and softness Cuteness Attention Cool and Warm factor were found out as constructing factors the Picture image combined Clothing and Ground 2) According to multidimensional positioning map were presented in a stimulus position the perceptive image differed in degree of similarity as a ground construction of stimulus in spite of same clothing image. It will aid in choosing the most beneficial background for any clothing brand. It will enhance the picture images to their full potential in any advertising medium.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.154-161
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• 2015

A novel multiframe super-resolution (SR) algorithm is presented to overcome the limitation of existing single-image SR algorithms using motion information from adjacent frames in a video. The proposed SR algorithm consists of three steps: i) definition of a local region using interframe motion vectors, ii) multiscale patch generation and adaptive selection of multiple optimum patches, and iii) combination of optimum patches for super-resolution. The proposed algorithm increases the accuracy of patch selection using motion information and multiscale patches. Experimental results show that the proposed algorithm performs better than existing patch-based SR algorithms in the sense of both subjective and objective measures including the peak signal-to-noise ratio (PSNR) and structural similarity measure (SSIM).

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.95-102
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• 2011

Interpolation schemes are used widely in image magnification. Magnified image generated by interpolation scheme is composed of the known pixels in input image and the interpolated pixels estimated from the known pixels in input image. So, as the interpolated pixels are estimated to have locality which exists in real images, the magnified image is much closer to the real image. In this paper, an efficient interpolation scheme was proposed to provide locality for the interpolated pixels by using the characteristics of adjacent pixels in input image. The quality of magnified image using the proposed scheme was improved. In experiment, PSNR(Peak Signal to Noise Ratio) was used to evaluate the performance of the proposed scheme. The PSNR's of the magnified images generated by the proposed scheme were greater than those of the magnified images generated by the previous interpolation methods.

• Journal of Conservation Science
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• v.37 no.3
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• pp.220-231
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• 2021

The use of digital copies of film-based analog images and the introduction of digital radiographic imaging systems using image plates gradually replace the non-destructive radiationirradiation method of Cultural Heritage. The quality of images obtained from this technique is affected by conditions such as tube voltage, tube current, and exposure time, type of image acquisition medium, distance of the artifacts from the image acquisition medium, and thickness of artifacts. In this study, we evaluated the grayscale image obtained using GE's Computed Radiograhpy (CR) imaging system, the transmission characteristics of the X-ray source for each tree type (pine, chestnut, sawtooth oak, ginkgo) used in wooden Cultural Heritage, and the signal-to-noise ratio (SNR) and contrast. The GE's CR imaging were analyzed using the Duplex wire image quality indicator, line-pair gauges.

• Journal of radiological science and technology
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• v.44 no.3
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• pp.225-229
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• 2021

The digital image such as medical X-ray and nuclear medicine field mainly contains noise distribution. The noise degree in image degrades image quality. That is why, the noise reduction algorithm is efficient for medical image field. In this study, we confirmed effectiveness of application for median modified Wiener filter (MMWF) algorithm for noise reduction in PET/MR image compared with median filter image, which is used as conventional noise redcution algorithm. The Jaszczak PET phantom was used by using 18F solution and filled with NaCl+NiSO4 fluids. In addition, the radioactivity ratio between background and six spheres in the phantom is maintained to 1:8. In order to mimic noise distribution in the image, we applied Gaussian noise using MATLAB software. To evlauate image quality, the contrast to noise ratio (CNR) and coefficient of variation (COV) were used. According to the results, compared with noise image and images with MMWF algorithm, the image with MMWF algorithm is increased approximately 33.2% for CNR result, decreased approximately 79.3% for COV result. In conclusion, we proved usefulness of MMWF algorithm in the PET/MR images.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2385-2388
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• 2005

In this paper, we propose the estimation method for the image affine information for computer vision. The first estimation method is given based on the XYS image normalization and the second estimation method is based on the image normalization by Pei and Lin. The XYS normalization method turns out to have better performance than the method by Pei and Lin. In addition, we show that rotation and aspect ratio information can be obtained using the central moments of both the original image and the sensed image. Finally, we propose the modified version of the normalization method so that we may control the size of the image.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1368-1370
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• 1996

The Information of Edges which takes small area comparing with the total image is very important in DNA images as well as general images. DNA image is the object should be managed by computing and it's demanding information is less than general images, but the accuracy is more important In a huge DNA image processing system such as DNA Information Bank, the performance depends on the size of image. In this paper, we extract the edge information and make it as a binary image. To reduce the size of the original image, it was applied by JPEG image compression method. The compressed image is combined with edge information when they are restored. As a result, Both the image compression ratio and restoration quality are optimized without the loss of critical information.