• Journal of the Korean Institute of Telematics and Electronics
• /
• v.23 no.5
• /
• pp.732-736
• /
• 1986

This paper propose a novel vector-quantized block truncation coder for image data compression. A data compression ratio of about 3-6 times larger than that of the BTC can be achieved by utilizign a vector quantizer with the BTC. A vector quantizer was realized by computer simulation. The compressed data rate of 0.7~1.0 bit/pel with intraframe coder and that of 0.3~0.5 bit/pel with interframe coder gives a good performance.

• Journal of Biomedical Engineering Research
• /
• v.15 no.1
• /
• pp.57-62
• /
• 1994

The demand of image compression is increasing now for the integration of medical images into the hospital information system. Even though the quantitative distortion can be measured from the difference between original and reconstructed images, it doesn't include the nonlinear characteristics of human visual system. In this study, we have evaluated the nonlinear characteristics of human visual system and applied them to the compression of medical images. The distortion measures which reflect the characteristics of human visual system has been considered. This image compression procedure consists of coding scheme using JND (Just Noticeable Difference) curve, polynomial approximation and BTC (Block Truncation Coding). Results show that this method can be applied to CT images, scanned film images and other kinds of medical images with the compression ratio of 5-10:1 without any noticeable distortion.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.6
• /
• pp.2817-2834
• /
• 2016

The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.6
• /
• pp.114-121
• /
• 2013

BTC image compression is a simple and easy hardware implementation, is widely used in a video compression techniques required for LCD overdrive. In this paper, methods for reducing compression loss, a multi-level quantization BTC (MLQ-BTC) algorithm is proposed. The process of the MLQ-BTC algorithm is, a input image is compressed and decompressed by Quasi 8-level method and Advanced 2-level BTC method, and select the algorithm with the smallest compression loss. Simulation results show that the proposed algorithm is efficient as compared with PSNR and compression ratio of the existing BTC methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.13 no.5
• /
• pp.390-399
• /
• 1988

A conventional BTC has the merit of real time processing and simple computation, but has the problem that its compression rate is low. In this paper, a modified BTC using the Quad Tree which is frequently used in binary image is proposed. The method results in the low compression rate by decreasing the total number of subblocks by mean of making the size of a subblock large in the small variation area of graty level and the size af a subblock small in the large variation area of gary level. For the effective transmission of bit plane, the Huffman run-lengh code for the large size of a subblock and the lookup table for tha small size of a subblock are used. The proposed BTC method show the result of coding 256 level image at the average data rate of about 0.8 bit/pixel.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.2
• /
• pp.140-146
• /
• 1989

An efficient quantization and encoding of BTC (Block Truncation Coding) parameters {($Y_{\alpha},\;Y_{\beta}),\;P_{{\beta}/{\beta}}$} are investigated, In our algorithm 4${\times}$4 blocks are classified into flat or edge block. While edge block is represented by two approximation level $Y_{\alpha},\;Y_{\beta}$ with label plane $P_{{\beta}/{\beta}}$, flat block is represented by single approximation level Y. The approximation levels Y, $Y_{\alpha}$ and $Y_{\beta}$ are encoded by predictive quatization specially designed, and the label plane $P_{{\beta}/{\beta}}$ is tried to be encoded using stored 32 reference plantes. The performance of the proposed scheme has appeared comparable to much more complex transform coding in terms of SNR, although it requires more study on the representation of small slope in background.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.1143-1144
• /
• 2008

본 논문에서는 motion-blur를 감소시키는 overdriving 기술의 오류를 감소시키기 위해 hybrid image coding 방법을 제안한다. hybrid image coding방법은 luminance data Y을 압축하기 위한 새로운 Adaptive Quantization Coding (AQC)을 제안하고 chrominance data CbCr을 Block Truncation Coding (BTC)방법으로 압축하는 것이다. 시뮬레이션 결과는 기존의 PSNR과 SD의 비교를 통하여 HIC의 우수함을 확인하여 알고리즘의 효율성을 검증하였다. 제안된 알고리즘은 verilog HDL를 통해 구조를 구현하고 synopsys design compiler를 통하여 합성 $0.13{\mu}m$ Samsung Library구조의 효율성을 확인하였다.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2005.07b
• /
• pp.863-864
• /
• 2005

In recent years, we use overdriving scheme to improve the response time of the liquid crystal. Since conventional overdriving scheme uses memory to perform ideal processing, it is desired to reduce system cost by decreasing the data stored in these SDRAMs. As a general compression method, quantization, sub-sampling and Block Truncation Coding ( BTC ) are used, which process data in block base and cause block effect. So we proposed new data compression method by color space conversion. Because this method compresses luminance and chrominance signal by different ratio, it can efficiently reduce error of block effect in decompression image.