• 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.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Korean Journal of Optics and Photonics
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• v.15 no.5
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• pp.429-434
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• 2004

An ophthalmic endoscope which is used in medical applications should have the total diameter less than 1 mm. Its image resolution is limited to 30∼40 lp/mm. Therefore, the image resolution is one of the most important factors to decide image quality of the ophthalmic endoscopic images. This study obtained high resolution and magnifying ophthalmic endoscopic images by a new optical design using a 0.23 pitch GRIN lens and high resolution fiber-optic image guide which has less than 5 ${\mu}{\textrm}{m}$ diameter microfibers. The resolutions of images from existing and from a new type of ophthalmic endoscope are measured and compared using a USAF resolution target.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.23-31
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• 2012

This paper proposes a motion estimation-based super resolution algorithm to restore input low-resolution images of large movement into a super-resolution image. It is difficult to find the sub-pixel motion estimation in images of large movement compared to typical experimental images. Also, it has disadvantage which have high computational complexity to find reference images and candidate images using general motion estimation method. In order to solve these problems for the traditional two-dimensional motion estimation using the proposed registration threshold that satisfy the conditions based on the reference image is determined. Candidate image with minimum weight among the best candidates for super resolution images, the restoration process to proceed with to find a new image registration algorithm is proposed. According to experimental results, the average PSNR of the proposed algorithm is 31.89dB and this is better than PSNR of traditional super-resolution algorithm and it also shows improvement of computational complexity.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.21-28
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• 2005

In this paper, we studied resolution to the FBP(Filtered Back-Propagation) tomographic image reconstruction algorithms. In order to analyze the resolution to the tomographic images, we derived ambiguity function to this algorithm which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system practically. Through simulation using this function, we determined the lateral and depth resolution quantitively and then analyzed respectively. Simulation results show that the lateral and depth resolution to the improved FBP image reconstruction algerian was determined $0.27\lambda\;and\;0.70\lambda$ at the 3dB, and also $0.89\lambda\;and\;0.96\lambda$ at the 6dB respectively. This results proved that improved FBP reconstruction algorithms for diffraction tomography of incident planar wave is useful to developed the tomographic image system, analyze the resolution to the tomographic images, we derived ambiguity function to this algerian which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system.

• Journal of Space Technology and Applications
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• v.3 no.3
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• pp.257-279
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• 2023

Korea Aerospace Research Institute has developed 6U Nano-Satellite high resolution video and image (HiREV) for the purpose of developing core technology for deep space exploration. The 6U HiREV Nano-Satellite has a mission of high-resolution image and video for earth observation, and the thermal pointing error between the lens and the camera module can occur due to the high temperature in camera module on mission mode. The thermal pointing error has a large effect on the resolution, so thermal design should solve it because the HiREV optical camera is developed based on commercial products that are the industrial level. So, when it operates in space, the thermal design is needed, because it has the best performance at room temperature. In this paper, three passive thermal designs were performed for the camera mission payload, and the thermal design was proved to be effective by performing on-orbit thermal analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1814-1828
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• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1738-1743
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• 2017

This paper presents an efficient image stitching method using preprocessing in order to generate a super resolution image. Two-dimensional (2D) scanners are consistently used in various areas but they have limitations such as paper sizes and materials. To overcome these problem with low-cost, an efficient imaging stitching method is proposed for producing a super resolution panorama image. To scan a very large sized paper using mobile phones, a simple portable cradle which fixes height is employed producing an input image set. To improve matching performance, a preprocessing method is introduced before searching correspondences. Then alpha blending is applied to an input image set to produce a super resolution panorama image. The proposed method is faster and easier than the existing method which is employed by Open CV. Experiment results show that the proposed method is three times faster and performs better than the existing method.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.270-274
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• 2015

In this paper, we propose an improved framework to analyze an N-ocular imaging system under fixed constrained resources such as the number of image sensors, the pixel size of image sensors, the distance between adjacent image sensors, the focal length of image sensors, and field of view of image sensors. This proposed framework takes into consideration, for the first time, the defocusing effect of the imaging lenses according to the object distance. Based on the proposed framework, the N-ocular imaging system such as integral imaging is analyzed in terms of depth resolution using two-point-source resolution analysis. By taking into consideration the defocusing effect of the imaging lenses using ray projection model, it is shown that an improved depth resolution can be obtained near the central depth plane as the number of cameras increases. To validate the proposed framework, Monte Carlo simulations are carried out and the results are analyzed.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.85-91
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• 2018

Computed tomography, which obtains section images from reconstruction process using projection images, has been applied to various fields. The spatial resolution of the reconstructed image depends on the device used in CT system, the object, and the reconstruction process. In this paper, we investigates the effect of the number of projection images and the pixel size of the detector on the spatial resolution of the reconstructed image under the parallel beam geometry. The reconstruction program was written in Visual C++, and the matrix size of the reconstructed image was $512{\times}512$. The numerical bar phantom was constructed and the Min-Max method was introduced to evaluate the spatial resolution on the reconstructed image. When the number of projections used in reconstruction process was small, artifact like streak appeared and Min-Max was also low. The Min-Max showed upper saturation when the number of projections is increased. If the pixel size of the detector is reduced to 50% of the pixel size of the reconstructed image, the reconstructed image was perfectly recovered as the original phantom and the Min-Max decreased as increasing the detector pixel size. This study will be useful in determining the detector and the accuracy of rotation stage needed to achieve the spatial resolution required in the CT system.