• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.10
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• pp.856-867
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• 2018

This paper presents the applicability of MIMO joint decoding to dual-contact satellite systems in which two LEO satellites using X-band frequency band are transmitting each image data to two ground station antennas, simultaneously. When two satellites are closely positioned within the looking angle of the two antennas, each satellite interferes with each other by the relative antenna gain corresponding to an offset angle and this might cause the performance degradation without interference mitigation. To mitigate the performance degradation, SM MIMO techniques for joint decoding are applied. Especially, the relative antenna gain of ground station depending on the angle difference between two satellites in ground station antenna plays an important role in modelling the dual-contact satellite systems. The condition number of MIMO channel including the antenna gain calculated from the mathematical gain pattern model was primarily analyzed. Simulation results showed that the SM MIMO techniques using detection schemes such as ZF-SIC, MMSE-SIC, and ML can be applicable to dual-contact satellite systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.229-235
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• 2024

Recent years have seen active research on methods for efficiently processing and interpreting large volumes of data in the fields of artificial intelligence and machine learning. One of these data processing technologies, Vector Symbolic Architecture (VSA), offers an innovative approach to representing complex symbols and data using high-dimensional vectors. VSA has garnered particular attention in various applications such as natural language processing, image recognition, and robotics. This study quantitatively evaluates the characteristics and performance of VSA methodologies by applying five VSA methodologies to the MNIST dataset and measuring key performance indicators such as encoding speed, decoding speed, memory usage, and recovery accuracy across different vector lengths. BSC and VT demonstrated relatively fast performance in encoding and decoding speeds, while MAP and HRR were relatively slow. In terms of memory usage, BSC was the most efficient, whereas MAP used the most memory. The recovery accuracy was highest for MAP and lowest for BSC. The results of this study provide a basis for selecting appropriate VSA methodologies depending on the application area.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.880-894
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• 1997

In this paper,we propose a new algorithm to perform DCT(Discrete Cosine Transform) withn the area reduced by prdeicting position of quantization coefficients to be zero.This proposed algorithm not only decreases the enoding time and the decoding time by reducing computation amount of FDCT(Forward DCT)and IDCT(Inverse DCT) but also increases comprossion ratio by performing each diffirent horizontal- vereical zig-zag scan assording to the calssified block size for each block on the huffiman coeing.Traditional image coding method performs the samd DCT computation and zig-zag scan over all blocks,however this proposed algorthm reduces FDCT computation time by setting to zero insted of computing DCT for quantization codfficients outside classfified block size on the encoding.Also,the algorithm reduces IDCT computation the by performing IDCT for only dequantization coefficients within calssified block size on the decoding.In addition, the algorithm reduces Run-Length by carrying out horizontal-vertical zig-zag scan approriate to the slassified block chraateristics,thus providing the improverment of the compression ratio,On the on ther hand,this proposed algorithm can be applied to 16*16 block processing in which the compression ratio and the image resolution are optimal but the encoding time and the decoding time take long.Also,the algorithm can be extended to motion image coding requirng real time processing.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.705-708
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• 2005

Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.69-72
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• 2005

As life style becomes to be complicated, lots of support technologies were developed. The bar code technology is one of them. It was renovating approach to goods industry. However, data storage ability in one dimension bar code came in limit because of industry growth. Two-dimension bar code was proposed to overcome one-dimension bar code. PDF417 bar code most commonly used in standard two-dimension bar codes is well defined at data decoding and error correction area. More works could be done in bar code image acquisition process. Applying various image enhancement algorithms, the recognition rate of PDF417 bar code is improved.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.293-297
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• 2013

Delivery of high quality video over a wide area network with large number of users poses great challenges for the video communication system. To ensure video quality, multiple descriptions have recently attracted various attention as a way of encoding and visual information delivery over wireless network. We propose a new efficient multiple description coding (MDC) technique. Quincunx lattice sub-sampling is used for generating multiple descriptions of an image. In this paper, we propose the application of a directional discrete cosine transform (DCT) to a sub-sampled quincunx lattice to create an MDC representation. On the decoder side, the image is decoded from the received side information. If all the descriptions arrive successfully, the image is reconstructed by combining the descriptions. However, if only one side description is received, decoding is executed using an interpolation process. The experimental results show that such the directional DCT can achieve a better coding gain as well as energy packing efficiency than the conventional DCT with re-alignment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5170-5188
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• 2015

This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.23-29
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• 2002

This paper suggest the image compression that is needed to process PACS in medical information system. The image decoding method is used Linear-predictor and Lloyd-Max quantizer(quantization) in the Wavelet transform domain. Wavelet Transform Method is processed the multi-resolution by dividing image into 10 sub-bands of 3 levels. Low frequency domain that is sensitive to human visual characteristic is encoded by DPCM which is lossless encoding methods, and Lloyed-Max quantizer, the optimal quantizer for reducing ringing and aliasing in the image of inter sub-band, is used in the remaining high frequency domain of sub-band. The examination verifies that decompressed images are superior by the result that PSNR is 28.53dB on the input image, 512$\times$152 abdominal CT image and Chest image.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.74-83
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• 2023

In this paper, we propose an image compression scheme which uses a demosaicking network and a channel-wise decoder in the decoding network. For the demosaicing network, we use as the input a colored mosaiced pattern rather than the well-known Bayer pattern. The use of a colored mosaiced pattern results in the mosaiced image containing a greater amount of information pertaining to the original image. Therefore, it contributes to result in a better color reconstruction. The channel-wise decoder is composed of multiple decoders where each decoder is responsible for each channel in the color image, i.e., the R, G, and B channels. The encoder and decoder are both implemented by wavelet based auto-encoders for better performance. Experimental results verify that the separated channel-wise decoders and the colored mosaic pattern produce a better reconstructed color image than a single decoder. When combining the colored CFA with the multi-decoder, the PSNR metric exhibits an increase of over 2dB for three-times compression and approximately 0.6dB for twelve-times compression compared to the Bayer CFA with a single decoder. Therefore, the compression rate is also increased with the proposed method than with the method using a single decoder on the Bayer patterned mosaic image.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.656-658
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• 2022

The purpose of infrared and visible image fusion is to integrate images of different modes with different details into a result image with rich information, which is convenient for high-level computer vision task. Considering many deep networks only work in a single scale, this paper proposes a novel image fusion based on three-scale dense network to preserve the content and key target features from the input images in the fused image. It comprises an encoder, a three-scale block, a fused strategy and a decoder, which can capture incredibly rich background details and prominent target details. The encoder is used to extract three-scale dense features from the source images for the initial image fusion. Then, a fusion strategy called l₁-norm to fuse features of different scales. Finally, the fused image is reconstructed by decoding network. Compared with the existing methods, the proposed method can achieve state-of-the-art fusion performance in subjective observation.