• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.568-577
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• 2017

IEEE Std 1609.2 was defined for the support of communication security functions in the WAVE (Wireless Access in Vehicular Environments) system. IEEE Std 1609.2 defined the message structures of the security services and managements on the vehicular communication by using ASN.1 (Abstract Syntax Notation One). Also, this security message structures shall be encoded using the COER (Canonical Octet Encoding Rules). In this paper, we designed and implemented the IEEE Std 1609.2 message encoder/decoder handling the security messages defined in IEEE Std 1609.2. The designed encoder/decoder consists of three modules as follows : a module generating the message of C language data structures in accord with IEEE Std 1609.2 message structures, a message encoder module, a message decoder module. And the encoder/decoder was implemented on the Linux environment. Also we analyzed the performance by measuring the performance speed of the encoder/decoder implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.511-516
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• 2006

In this raper, we propose the Sequentiel Couleur Avec Memoire or Sequential Color with Memory (SECAM) video encoder system using modified anti-cloche filters and the SECAM video decoder system using a band pass filter (BPF) and an error-free square root. The SECAM encoder requires an anti-cloche filter recommended by International Telecommunication Union-Recommendation (ITU-R) Broadcasting service Television (BT) 470. However, the design of the anti-cloche filter is difficult because the frequency response of the anti-cloche filter is very sharp around rejection-frequency area. So, we convert the filter into a hish pass filter (HPF) by shifting the rejection frequency of 4.286MHz to 0Hz frequency. The design of HPF becomes very easy, compared to that of the anti-cloche filter. The proposed decoder also uses an error-free square root, two differentiators and trigonometric functions to extract color-component information of Db and Dr accurately from frequency modulation (FM) signals in SECAM systems. Also, the BPF in decoder it used for removing color noise in chrominance and dividing CVBS into chrominance and luminance. The proposed systems are experimentally demonstrated with Altera FPGA APEX20KE EP20K1000EBC652-3 device and TV sets.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.849-857
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• 2018

In this paper, we propose an automatic composition method using time series embedding of RNN Auto-Encoder. RNN Auto-Encoder can learn existing songs and can compose new songs from the trained RNN decoder. If one song is fully trained in the RNN Auto-Encoder, the song is embedded into the vector values of RNN nodes in the Auto-Encoder. If we train a lot of songs and apply a specific vector to the decoder of Auto-Encoder, then we can obtain a new song that combines the features of trained multiple songs according to the given vector. From extensive experiments we could find that our method worked well and generated various songs by selecting of the composition vectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1689-1703
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• 2020

When data is transmitted over an unreliable channel, the error of the data packet may result in serious degradation. The multiple description coding (MDC) can solve this problem and save transmission costs. In this paper, we propose a deep multiple description coding network (MDCN) to realize efficient image compression. Firstly, our network framework is based on convolutional auto-encoder (CAE), which include multiple description encoder network (MDEN) and multiple description decoder network (MDDN). Secondly, in order to obtain high-quality reconstructed images at low bit rates, the encoding network and decoding network are integrated into an end-to-end compression framework. Thirdly, the multiple description decoder network includes side decoder network and central decoder network. When the decoder receives only one of the two multiple description code streams, side decoder network is used to obtain side reconstructed image of acceptable quality. When two descriptions are received, the high quality reconstructed image is obtained. In addition, instead of quantization with additive uniform noise, and SSIM loss and distance loss combine to train multiple description encoder networks to ensure that they can share structural information. Experimental results show that the proposed framework performs better than traditional multiple description coding methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.653-669
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• 2024

Dynamic scene deblurring is a complex computer vision problem owing to its difficulty to model mathematically. In this paper, we present a novel approach for image deblurring with the help of the sharp reference image, which utilizes the reference image for high-quality and high-frequency detail results. To better utilize the clear reference image, we develop an encoder-decoder network and two novel modules are designed to guide the network for better image restoration. The proposed Reference Extraction and Aggregation Module can effectively establish the correspondence between blurry image and reference image and explore the most relevant features for better blur removal and the proposed Spatial Feature Fusion Module enables the encoder to perceive blur information at different spatial scales. In the final, the multi-scale feature maps from the encoder and cascaded Reference Extraction and Aggregation Modules are integrated into the decoder for a global fusion and representation. Extensive quantitative and qualitative experimental results from the different benchmarks show the effectiveness of our proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.371-381
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• 2005

In this paper, we propose an advanced hardware architecture for the CAVLC entropy encoder/decoder engine for real time video compression. The CAVLC (Context-based Adaptive Variable Length Coding) is a lossless compression method in H.264/AVC and it has high compression efficiency but has computational complexity. The reference memory size is optimized using partitioned storing method and memory reuse method which are based on partiality of memory referencing. We choose the hardware architecture which has the most suitable one in several encoder/decoder architectures for the mobile devices and improve its performance using parallel processing. The proposed architecture has been verified by ARM-interfaced emulation board using Altera Excalibur and also synthesized on Samsung 0.18 um CMOS technology. The synthesis result shows that the encoder can process about 300 CIF frames/s at 150MHz and the decoder can process about 250 CIF frames/s at 140Mhz. The hardware architectures are being used as core modules when implementing a complete H.264/AVC video encoder/decoder chip for real-time multimedia application.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.112-121
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• 2010

Distributed video coding is a coding paradigm that allows complexity to be shared between encoder and decoder, in contrast with conventional video coding. We propose that complexity balancing method of encoder/decoder by phase motion estimation algorithm. The encoder performs partial motion estimation. The result of the partial motion estimation is transferred to the decoder, and the decoder performs motion estimation within the narrow range. When the encoder can afford some complexity, complexity balancing is possible. The method proposed is able to know relativity between complexity balancing and coding efficiency. The coding efficiency increase rate by the encoder complexity increases is higher than that by the decoder complexity increases. The proposed method can control the complexity and coding efficiency according to devices' resources and channel conditions.

• Journal of Digital Contents Society
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• v.6 no.3
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• pp.169-174
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• 2005

In this paper we propose efficient design and implementation of JPEG image display board that can display JPEG image on TV. we used NAND Flash Memory to save the compressed JPEG bit stream and video encoder to display the decoded JPEG mage on TV. Also we convert YCbCr to RGB to super impose character on JPEG image. The designed B/D is implemented using FPGA.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.47-57
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• 2021

Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.