• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.865-869
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• 2009

An image resolution enhancement is mainly utilized as pre-processing technique for various image processing application. It requires to decrease image quality deterioration such as blurring. In this paper, we propose an image resolution enhancement algorithm using low level interpolation. In the proposed algorithm, we calculate an error using low level interpolation, estimate an error image from the calculated error. The estimated error image is added interpolated high resolution image, it become lastly reconstruction image. Our experiments obtained the average PSNR about 1dB which is improved results better than conventional method for sensitive image quality. Also, subjective image quality with edge region is more clearness. The proposed method may be helpful for applications in various multimedia systems such as image restoration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.361-369
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• 1998

Recently, the improvement of on-board satellite sensors covering hyperspectral image sensors, high spatial resolution sensors provide data on earth in diverse aspect. The application field relating remotely sensed data also varies depending on what type of job one wants. The various resolution of sensors from low to extremely high is also available on the market with a user defined specific location. The expense to purchase remote sensed data is going down compare to the cost it need past few years ago in terms of research or private use. Now, the satellite remote sensed data is used on the field of forecasting, forestry, agriculture, urban reconstruction, geology, or other research field in order to extract meaningful information by applying special techniques of image processing. There are many image processing packages available worldwide and one common aspect is that they are expensive. There need to be a advanced satellite data processing package for people who can not afford commercial packages to apply special remote sensing techniques on their data and produce valued-added product. The study was carried out with the purpose of developing a special satellite data processing package which covers almost every satellite produced data with normal image processing functions and also special functions needed on specific research field with friendly graphical user interface (GUI). And for the people with any background of remote sensing with windows platform.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.1
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• pp.13-18
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• 2008

Purpose: The image processing method due to the algorism which is various portion nuclear medical image decision is important it makes holds. The purpose of this study is it applies hereupon new image processing method SIEMENS (made by Pixon co.) Onco. flash processing reconstruction and the comparison which use the image control technique of existing the clinical usefulness it analyzes with it evaluates. Materials & Methods: 1. Whole body bone scan-scan speed 20 cm/min, 30 cm/min & 40 cm/min blinding test 2. Bone static spot scan-regional view 200 kcts, 400 kcts for chest, pelvis, foot blinding test 3. 4 quadrant-bar phantom-20000 kcts visual evaluation 4. LSF-FWHM resolution comparison ananysis. Results: 1. Raw data (20 cm/min) & processing data (30 cm/min)-similar level image quality 2. Low count static image-image quality clearly improved at visual evaluation result. 3. Visual evaluation by quadrant bar phantom-rising image quality level 4. Resolution comparison evaluation (FWHM)-same difference from resolution comparison evaluation Conclusion: The study which applies a new method Onco. flash processing reconstruction, it will be able to confirm the image quality improvement which until high level is clearer the case which applies the method of existing better than. The new reconstruction improves the resolution & reduces the noise. This enhances the diagnostic capabilities of such imagery for radiologists and physicians and allows a reduction in radiation dosage for the same image quality. Like this fact, rising of equipment availability & shortening the patient waiting move & from viewpoint of the active defense against radiation currently becomes feed with the fact that it will be the useful result propriety which is sufficient in clinical NM.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.407-414
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• 2014

The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.503-512
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• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.243-252
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• 2005

Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.792-797
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• 2002

In the following paper two algorithms, suitable for the analysis of panchromatic data as provided by KOMPSAT-1 will be presented. One is a texture analysis which will be used to create a settlement mask based on the variations of gray values. The other is a fusion algorithm which allows the combination of high resolution panchromatic data with medium resolution multispectral data. The procedure developed for this purpose uses the spatial information present in the high resolution image to spatially enhance the low resolution image, while keeping the distortion of the multispectral information to a minimum. This makes it possible to use the fusion results for standard multispecatral classification routines. The procedures presented here can be automated to large extent, making them suitable for a standard processing routine of satellite data.