• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.198-206
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• 2022

This paper proposes a method to solve problems that may occur when SPIHT(set partition in hierarchical trees) is used in a dedicated codec for compressing complex holograms with ultra-high resolution. The development of codecs for complex holograms can be largely divided into a method of creating dedicated compression methods and a method of using anchor codecs such as HEVC and JPEG2000 and adding post-processing techniques. In the case of creating a dedicated compression method, a separate conversion tool is required to analyze the spatial characteristics of complex holograms. Zero-tree-based algorithms in subband units such as EZW and SPIHT have a problem that when coding for high-resolution images, intact subband information is not properly transmitted during bitstream control. This paper proposes a method of dividing wavelet subbands to solve such a problem. By compressing each divided subbands, information throughout the subbands is kept uniform. The proposed method showed better restoration results than PSNR compared to the existing method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.109-114
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• 2023

In this paper, a 2-channel Image-Reject receiver using a 65-nm CMOS process is presented for Ka-band compact radars. The designed receiver consists of Low-Noise Amplifier (LNA), IQ mixer, and Analog Baseband (ABB). ABB includes a complex filter in order to suppress unwanted images, and the variable gain amplifiers (VGAs) in RF block and ABB have gain tuning range from 4.5-56 dB for wide dynamic range. The gain of the receiver is controlled by on-chip SPI controllers. The receiver has noise figure of <15 dB, OP1dB of >4 dBm, image rejection ratio of >30 dB, and channel isolation of >45 dB at the voltage gain of 36 dB, in the Ka-band target frequency. The receiver consumes 420 mA at 1.2 V supply with die area of 4000×1600 ㎛.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.185-205
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• 2014

SAR ground moving target indicator (GMTI) has long been an important issue for SAR advanced applications. As spatial resolution of space-borne SAR system has been significantly improved recently, the GMTI becomes a very useful tool. Various GMTI techniques have been developed particularly using multi-channel SAR systems. It is, however, still problematic to detect ground moving targets within single channel SAR images while it is not practical to access high resolution multi-channel space-borne SAR systems. Once a ground moving target is detected, it is possible to retrieve twodimensional velocities of the target from single channel space-borne SAR with an accuracy of about 5 % if moving faster than 3 m/s. This paper presents a quick-and-dirty method for detecting ground moving targets from single channel SAR single-look complex (SLC) images by differentiation. Since the signal powers of derivatives present Doppler centroid and rate, it is very efficient and effective for detection of non-stationary targets. The derivatives correlate well with velocities retrieved by a precise method with a correlation coefficient $R^2$ of 0.62, which is well enough to detect the ground moving targets. While the approach is theoretically straightforward, it is necessary to remove the effects of residual Doppler rate before finalizing the ground moving target candidates. The confidence level of results largely depends on the efficiency and effectiveness of the residual Doppler rate removal method. Application results using TerraSAR-X and truck-mounted corner reflectors validated the efficiency of the method. While the derivatives of moving targets remain easily detectable, the signal energy of stationary corner reflectors was suppressed by about 18.5 dB. It results in an easy detection of ground targets moving faster than 8.8 km/h. The proposed method is applicable to any high resolution single channel SAR systems including KOMPSAT-5.

• Journal of Biomedical Engineering Research
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• v.33 no.2
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• pp.72-77
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• 2012

Phase Contrast MR Angiography(PC MRA) is excellent MRA technique for measuring the velocity of vessels in the human body. PC MRA need to at least four images for angiogram reconstruction and it caused longer scan time. Therefore, we used keyhole imaging combined PC MRA to reduce the scan time. However, keyhole imaging can lead the erroneous effects as loss of phase information or frequency discontinuous. In this study, we applied the keyhole imaging combined 2D PC MRA for improving the temporal resolution and also measured the velocity to evaluate the accuracy of phase information. We used 0.32T MRI scanner(Magfinder II, Scimedix, Korea). Using the 2D PC MRA pulse sequence, the vascular images for a human brain targeted on the Superior Sagittal Sinus(SSS) were obtained. We applied tukey window function for keyhole images to minimize the ringing artifact and erroneous factors that are induced frequency discontinuous and phase information loss. We also applied zero-padded algorithm to peripheral missing k-space lines to compare keyhole imaging results and the artifact power(AP) value was measured on the complex difference images to validate the image quality. Consider as based on our results, heavy image distortions and artifacts were shown until using at least 50% keyhole factor. Using above the 50% keyhole factors are shown well reconstructed and matched for magnitude images and velocity information measurements. In conclusion, we confirmed the image quality and velocity information of keyhole technique combined 2D PC MRA. Especially, measured velocity information through the keyhole imaging combination was similar to the velocity information of full sampled k-space image despite of frequency discontinuous and phase information loss in the keyhole imaging reconstruction process. Consequently, the keyhole imaging combined 2D PC MRA will give some clinical usefulness and advantages as improving the temporal resolution and measuring the velocity information via selecting the appropriate keyhole factor at low tesla MRI system.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.175-179
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• 2016

Recent advances in technology of medical image have made surgical simulation that is helpful to diagnosis, operation plan, or education. Improving and enhancing the medical imaging have led to the availability of high definition images and three-dimensional (3D) visualization, it allows a better understanding in the surgical and educational field. The Real human field of view is stereoscopic. Therefore, with just 2D images, stereoscopic reconstruction process through the surgeon's head, is necessary. To reduce these process, 3D images have been used. 3D images enhanced 3D visualization, it provides significantly shorter time for surgeon for judgment in complex situations. Based on 3D image data set, virtual medical simulations, such as virtual endoscopy, surgical planning, and real-time interaction, have become possible. This article describes principles and recent applications of newer imaging techniques and special attention is directed towards medical 3D reconstruction techniques. Recent advances in technology of CT, MR and other imaging modalities has resulted in exciting new solutions and possibilities of shoulder imaging. Especially, three-dimensional (3D) images derived from medical devices provides advanced information. This presentation describes the principles and potential applications of 3D imaging techniques, simulation and printing in shoulder and elbow practice.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.57-59
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• 1998

For medical students and doctors, knowledge of the three-dimensional (3D) structure of brain is very important in diagnosis and treatment of brain diseases. Two-dimensional (2D) tools (ex: anatomy book) or traditional 3D tools (ex: plastic model) are not sufficient to understand the complex structures of the brain. However, it is not always guaranteed to dissect the brain of cadaver when it is necessary. To overcome this problem, the virtual dissection programs of the brain have been developed. However, most programs include only 2D images that do not permit free dissection and free rotation. Many programs are made of radiographs that are not as realistic as sectioned cadaver because radiographs do not reveal true color and have limited resolution. It is also necessary to make the virtual dissection programs of each race and ethnic group. We attempted to make a virtual dissection program using a 3D image of the brain from a Korean cadaver. The purpose of this study is to present an educational tool for those interested in the anatomy of the brain. The procedures to make this program were as follows. A brain extracted from a 58-years old male Korean cadaver was embedded with gelatin solution, and serially sectioned into 1.4 mm-thickness using a meat slicer. 130 sectioned specimens were inputted to the computer using a scanner ($420\times456$ resolution, true color), and the 2D images were aligned on the alignment program composed using IDL language. Outlines of the brain components (cerebrum, cerebellum, brain stem, lentiform nucleus, caudate nucleus, thalamus, optic nerve, fornix, cerebral artery, and ventricle) were manually drawn from the 2D images on the CorelDRAW program. Multimedia data, including text and voice comments, were inputted to help the user to learn about the brain components. 3D images of the brain were reconstructed through the volume-based rendering of the 2D images. Using the 3D image of the brain as the main feature, virtual dissection program was composed using IDL language. Various dissection functions, such as dissecting 3D image of the brain at free angle to show its plane, presenting multimedia data of brain components, and rotating 3D image of the whole brain or selected brain components at free angle were established. This virtual dissection program is expected to become more advanced, and to be used widely through Internet or CD-title as an educational tool for medical students and doctors.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.131-146
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• 1999

The satellite visible data have been successfully applied to study the ocean color. Another ocean color sensor, the Ocean Scanning Multi-spectral Imager (OSMI) on the Korea Multi-Purpose Satellite (KOMPSAT) will be launched in 1999. In order to understand the characteristics of future OSMI images, we have first discussed the simulation models and procedures in detail, and produced typical patterns of radiances at visible bands by using radiative transfer models. The various simulated images of full satellite passes and Korean local areas for different seasons, water types, and the satellite crossing equator time (CET) are presented to illustrate the distribution of each component of radiance (i.e., aerosol scattering, Rayleigh scattering, sun glitter, water-leaving radiance, and total radiance). A method to evaluate the image quality and availability is then developed by using the characteristics of image defined as the Complex Signal Noise Ratio (CSNR). Meanwhile, a series of CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of OSMI images before the KOMPSAT will be placed in orbit. Finally, the quality and availability of OSMI images are quantitatively analyzed by the simulated CSNR image. It is hoped that the results would be useful to all scientists who are in charge of OSMI mission and to those who plan to use the data from OSMI.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.91-102
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• 2004

This paper reflects the estimation of using the EOC(Electro-optical Camera) images supporting GIUH(geomorphological instantaneous unit hydrograph) approach. We have analyzed GIUH in its density and frequency distribution by creating a DEM(digital elevation model) for the sub basin produced from the EOC images and examined topographical and hydrological application possibility of the EOC images. In this process, we have topographical basin characteristic analysis that use the remote sensing technique analyzing the DEM creation process of the EOC stereo images by studying the basic topographical hydrology analysis about abstraction technique since it is flirty complex and is more time-consuming than other method. we executed statistical analysis of a basin size and river length using the frequency function after divided lattice spacing applied have to the sub river basin from the image data and the digital map into 10m intervals ranging from 10m to 100m. After comparing and examining the peak and time to peak of the GIUH, we proceeded with a comparative analysis by lattice concerning the topographical divergence rate, area ratio, length ratio. Accumulating the peak and time to peak of the GIUH is altered to non-linear form in accordance to lattice dimension as well as basin factor. It was proved that the lattice dimension is one of the important factors about the peak and time to peak of the GIUH.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.