• Journal of KIISE:Databases
• /
• v.30 no.5
• /
• pp.429-437
• /
• 2003

Over the last decades, improvements in CPU speed have greatly exceeded those in memory and disk speeds by orders of magnitude and this enabled the use of compression techniques to reduce the database size as well as the query cost. Although compression techniques are employed in various database researches, there is little work on compressing multi-dimensional index structures. In this paper, we propose an efficient compression method called the hybrid encoding method (HEM) that is tailored to multi-dimensional indexing structures. The HEM compression significantly reduces the query cost and the size of multi-dimensional index structures. Through mathematical analyses and extensive experiments, we show that the HEM compression outperforms an existing method in terms of the index size and the query cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.05a
• /
• pp.268-272
• /
• 2003

Large medical images in PACS are compressed for saving storage space and improving network speed. The integrated compression environment was designed and developed for uniting of various compression methods. Various compression algorithm-RLE compression, lossless JEPG, JPEG, was built into it, complying with DICOM. A image compression using DWT was also implemented in it. And a unified algorithm of lossless compression and lossy compression was designed to improve images quality and to make compression ratios high. And integrated compression environment was operating together with a database program for efficient and user-friendly management.

• Proceedings of the IEEK Conference
• /
• 2000.11d
• /
• pp.267-270
• /
• 2000

In this paper, we describe implementation of efficient wavelet image compression and decompression system for DVR(Digital Video Recoder). We used various methods to remove time redundancy, spatial redundancy and statistical redundancy of video camera inputs. Motion detection, wavelet transform, RLC(Run Length Coding) and huffman coding techniques are combined for efficient compression / decompression.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.7
• /
• pp.1624-1632
• /
• 1996

Wavelet transform is widely used for high compression ratio image compression. It requeires a large memory when it is implemented by a hardware. Therefore, it is efficient to divide the entire image into blocks. Because the wavelet transform for divided blocks causes losses, pixels of the adjacent blocks are used. In the case of color image compression, the image is decomposed into brightness and color components, and then color components are downsampled. When the wavelet transform is performed by using pixels of adjacentblocks, the number of necessary pixels are doubled due to downsampling of color components. In this paper, we propose an efficient block wavelet transform using variablefilter length for brightness and color components. By using the proposed method, the number of pixels of adjacent blocks is optimized. We show the degradation of image quality due to the reduction of filter length for color components is negligible through simulations.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.11a
• /
• pp.187-190
• /
• 2004

This paper proposes an efficient hardware implementation of SPIHT(Set Partitoning In Hierarchical Tree) algorithm for image compression with the discrete wavelet transform. An efficient technique to scan the coefficients which are located in partitioned spatial orientation trees by DWT is considered in terms of counter fields for sorting pass and refinement pass. The proposed image compression method using SPIHT has been modeled in VHDL and has been implemented by use of both TMS320C6000 as a DSP and Virtex2 as a Xilinx FPGA.

• Journal of KIISE:Computing Practices and Letters
• /
• v.10 no.3
• /
• pp.243-250
• /
• 2004

We describe a practical implementation of DVR (Digital Video Recording) system. And we propose a new image compression algorithm, that input video signal is divided into two parts, a moving target and a non-moving background part to achieve efficient compression of image sequences. This algorithm reorganizes a target area and a back-ground area by use of Macro Block(MB) unit on encoding scheme. The proposed algorithm allows high quality image reconstruction at low bit rates.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.6 no.2
• /
• pp.11-17
• /
• 2010

In this paper, we propose efficient rate control algorithm for video near-lossless compression. The proposed method adjusts pixel error range using amounts of previous encoded bits and target bits at a slice encoding interval. Thus, encoded bits by the proposed method are transmitted well through limited bandwidth without overflow. Also, target bits and encoded bits can be controlled according to transmission policy. Experimental results show that our proposed method not only almost fits compression ratio, but also has better image quality.

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.10
• /
• pp.371-376
• /
• 2014

Consistently collecting a variety of vital signs is crucial in u-Healthcare. In order to do so, IoT is being considered as a top solution nowadays as an efficient network environment between the sensor and the server. This paper proposes a transmission method and compression algorithm which are appropriate for IoT environment. Results were compared to widely used compression methods, and were compared to other prior researches. The results showed that the compression ratio of our proposed algorithm was 11.7.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3823-3840
• /
• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.2C
• /
• pp.186-193
• /
• 2009

Multi-view video is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method by presentation of efficient layered depth image using real distance comparison, solution of overlap problem, and YCrCb color transformation. In experimental results, confirmed high compression performance and good reconstructed image.