• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.39-44
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• 1998

Determining the absolute location of a mobile robot is essential in the navigation of a mobile robot. In this paper, a method to determine the position of a mobile robot through the visual image of a landrnark using neural networks is proposed. In determining the position of a mobile robot on the world coordinate, there is a position error because of uncertainty in pixels, incorrect camera calibration and lens distortion. To reduce the errors, a method using a BPNN(Back Propagation Neural Network) is proposed. The experimental results are presented to illustrate the superiority of the proposed method when comparing with the conventional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1205-1214
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• 2013

Recently spaceborne SAR systems are increasing image resolution and frequency. As a high quality image resolution, the wider bandwidth is required and a wideband signal generator with RF component is very complicated and RF impairments of device is increased. Therefore, it is very important to improve performance by reducing these errors. In this study, the transmission signal of the wideband signal generator is applied to the phase noise, IQ imbalance, ripple gain, nonlinear model of high power amplifier. And we define possible structures of wideband signal generator and measure the PSLR and ISLR for the performance assesment. Also, we extract error of the amplitude and phase from the waveform and use a quadratic polynomial curve fitting and examine the performance change due to nonlinear device. Finally, we apply a high power amplifier predistortion method for non-linear error compensation. And we confirm that distortion in the output of the amplifier by intermodulation component is decreased by 15 dB.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.14-22
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• 2011

The conventional satellite image fusion methods usually add the same amount of higher frequency components extracted from the panchromatic image to all the multispectral images. However, it is noted that each of multispectral images has different amount of overlap with the panchromatic image in terms of its spectrum, and also has different intensities. Thus giving the same amount of high frequency contents to all the spectral bands does not match with this observation, which causes color distortion in the fused image. In this paper, we propose a new wavelet-domain satellite image fusion algorithm that can compensate for these differences in intensity and spectrum overlap. For the compensation of intensity differences, we first estimate the high resolution multispectral images from P, considering the relative intensity ratios. For the compensation of the amount of spectral overlap, their wavelet coefficients are appended to the conventional wavelet-domain method where the coefficients for the addition is determined by the amount of spectrum overlap. Experiments are conducted for the IKONOS satellite images whose spectrums are well known, and the results show that the proposed algorithm gives higher PSNR and correlation coefficients compared to the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.132-145
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• 2009

We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.153-159
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• 2024

In X-ray projection, Unskilled radiologists become skilled through fail exam. This causes the patient to be exposed to unnecessary radiation. In this study, pre-position unskilled radiologic technologist presented ways to improve clinical proficiency. presented a skull lateral x-ray projection practice method using visual, spatial, and assistive devices. In addition, the accuracy and usefulness of the use of assistive devices were evaluated. When X-ray images were taken based on learning, the rotational spacing, which indicates image distortion, was 7.85 ± 1.45 mm and the tiliting spacing was 4.84 ± 0.5 mm. When practicing using visual aids, the rotational spacing is 4.4 ± 0.76 mm and the inclination spacing is 3.01 ± 0.87 mm. using a spatial compensation device, the rotational spacing is 5.2 ± 0.69 mm and the tiliting spacing is 3.33 ± 0.61 mm. Skull lateral X-ray Image distortion caused by empirical photography practice decreased by 5.4%, but image distortion caused by tilting increased by 1.2%. When practicing using a visual assistive devices, the degree of rotational spacing by 40.1% and the tiliting spacing decreased by 30.7% compared to the empirical x-ray exposure practice. When using spatial assistive devices, the rotation interval was reduced by 41.7% and the tilting interval by 23.7% compared to conventional empirical x-ray exposure practice. Therefore, if an unskilled radiologist practices using visual and spatial aids,the accuracy will be improved in skull lateral x-ray projection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.575-584
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• 2002

This paper presents a novel DCT-based embedded zero-tree coding and optimal bit allocation algorithm for image sequence coding. In order to fully utilize the structure of the conventional standard coding algorithm and improve the coding efficiency, motion estimation and compensation(ME/MC)-DCT hybrid coding structure and a modified zero-tree coding algorithm are applied. After the rearrangement DCT coefficients into pyramidal structure according to their significance on the decoded image quality, the modified embedded zero-tree coding is performed on layered coefficients. Moreover, for a given overall bit rates, a new optimal bit control scheme is proposed to achieve the best decoded image quality in the consecutive frames. The rate control scheme can also provide the equal quality of decoded image with the control of bit rate and distortion for each frame. The various simulation results are provided to evaluate the coding performance of the proposed scheme.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.117-126
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• 2008

In this paper, it is presented a digital image processing method and the program (Visual C++) to determine the shape of the suspension bridge. To investigate the precision of this method, a suspension bridge is divided into 5, 13 and 19 images, respectively, by using the 6.3M pixels digital camera with 300mm zoom lens. Obtained results of the Kwang-Ahn Grand Bridge by using this method are fairly close to the real precision surveyed data. The accuracy is more improved by increasing the number of divided images of the structure. The total cost, man power and time of field survey by this method presented in this study could be much more reduced and the developed program could be applied with little modification for other structures like cable-stayed bridges, if lens compensation algorithms and program access capabilities are improved.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.59-68
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• 2005

This paper proposes a face recognition under varying poses using local area obtained by side-view pose normalization. General normalization methods for face recognition under varying pose have a problem with the information about invisible area of face. Generally this problem is solved by compensation, but there are many cases where the image is distorted or features lost due to compensation .To solve this problem we normalize the face pose in side-view to reduce distortion that happens mainly in areas that have large depth variation. We only use undistorted area, removing the area that has been distorted by normalization. We consider two cases of yaw pose variation and pitch pose variation, and by experiments, we confirm the improvement of recognition performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.375-382
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• 2010

In this paper, we propose the simplified and improved system of One Color Detector to protect color distortion of simple color images in the processed of Auto White Balance (AWB). The proposed One Color Detector is based on Grayworld algorithm which controls color compensation except one color in simple image and widely applies for mobile phone camera because of high efficiency. This system can be suitable for diverse image size, and let user control the threshold in diverse size and environments compared with conventional system. Also the hardware size of the proposed system is reduced by 80% over that of the conventional one.