• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.11-16
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• 2014

Block truncation coding (BTC) is a recent technique used for compression of monochrome image data. The original algorithm of BTC implement to use the standard mean and the standard deviation. For data hiding, it is needed to modify bit-planes of an images. These modifications yields unacceptable quality of BTC images. Thus, we propose IODBTC (Improved Ordered dithering BTC) improving BTC. In this paper, we improve this problem. Experimental results show that the reconstructed secret messages are the same as the original secret messages, and that the proposed scheme exhibits a good BTC images compared to that of previous schemes.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.67-74
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• 2015

BTC (Block Truncation Coding) image compression is simple to implement by hardware and has excellent edge retention capability of image, image compression techniques are widely used in LCD overdrive. In this paper, to maintain high visual quality and has high compression rate, Multi-Mode BTC (MM-BTC) algorithm is proposed. The MM-BTC has high compression rate using advanced Y-based BTC method and has high visual quality using improved 2-level and 4-level BTC method in this paper. As shown in simulation results, MM-BTC improves still image PSNR (Peak Signal to Noise Ratio) up to 2.34 dB as compared with other algorithms. When the MM-BTC is applied to LCD overdrive, MM-BTC improves moving picture PSNR up to 2.33 dB as compared with other algorithms in literature.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.114-121
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• 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 the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.77-83
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• 2015

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.135-141
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• 2012

To reduce frame memory size usage in LCD overdrive, block truncation coding (BTC) image compression is commonly used. For maximization of compression ratio, BTC image compression is need to compress bitmap or quantization data. In this paper, for high compression ratio, we propose CMBQ-BTC (CMBQ : compression method bitmap data and quantization data) algorithm. Experimental results show that proposed algorithm is efficient as compared with PSNR and compression ratio of the conventional BTC method.

• Bulletin of the Korean Chemical Society
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• v.30 no.12
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• pp.2921-2926
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• 2009

Cu-BTC[$Cu_3(BTC)_2(H_2O)_3$, BTC = 1,3,5-benzenetricarboxylate], one of the most well-known metal-organic framework materials (MOF), has been synthesized under atmospheric pressure and room temperature by using ultrasound. The Cu-BTC can be obtained in 1 min in the presence of DMF (N,N-dimethylformamide), suggesting the possibility of continuous production of Cu-BTC. Moreover, the surface area and pore volume show that the concentration of DMF is important for the synthesis of Cu-BTC having high porosity. The morphology and phase also depend on the concentration of DMF : Cu-BTC cannot be obtained at room temperature in the absence of DMF and aggregated Cu-BTC (with low surface area) is produced in the presence of high concentration of DMF. It seems that the deprotonation of benzenetricarboxylic acid by base (such as DMF) is inevitable for the room temperature syntheses.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.3
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• pp.30-36
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• 2012

block truncation coding(BTC) image compression is known as a simple and efficient technology for image compression algorithm. In this paper, we propose RMC-BTC algorithm(RMC : reduction method chrominace data) for color image compression. To compress chrominace data, in every BTC block, the RMC-BTC coding employs chrominace data expressed with average of chrominace data and using method of luminance data bit-map to represented chrominance data bit-map. Experimental results shows efficiency of proposed algorithm, as compared with PSNR and compression ratio of the conventional BTC method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.515-521
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• 2022

In this paper, we propose Quad BTC that compresses DSM files to allow random access for TRF (Terrain Referenced Flight). The terrain data used for TRF has a large data capacity to be stored in the UAV (Unmanned Aerial Vehicle), so its size must be reduced through compression. Conventional BTC (Block Truncation Coding) based compression methods are suitable for TRF because it can decode randomly accessing specific coordinates. However, These conventional methods have a problem that the error increases because the deviation of the data increases as the size of the block increases. In this paper, we propose Quad BTC method that adaptively divides a block in to 4 sub blocks and compresses to solve this problem. The proposed method may reduce errors because the size of the sub block can be adjusted within the block. Through simulation using actual terrain data, it is verified that Quad BTC has less error at the same compression ratio than conventional BTC and AM BTC.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.51-57
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• 2010

In this paper, It propose methods compressing BTC image utilizing data hiding technique. BTC is used to compress general digital image into binary image and applied into application such as printer. Additional information, transferred with binary image, is as big as the size of binary image. Therefore, we wish to reduce the total transmission bandwidth by decreasing the additional information with sustaining the small image degradation. Because typical BTC image doesn't have enough space for data hiding, we adopt Adaptive AMBTC (Absolute Moment BTC) algorithm to produce the binary image, and calculate virtual histogram from created binary image and modify this histogram for reducing the additional information. The proposed algorithm can reduce about 6-11 % of the image file size, compared with the existing BTC algorithm, without making perceptible image degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1499-1513
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• 2014

This paper proposes a novel blind image watermarking scheme exploiting Block Truncation Coding (BTC). Most of existing BTC-based watermarking or data hiding methods embed information in BTC compressed images by modifying the BTC encoding stage or BTC-compressed data, resulting in watermarked images with bad quality. Other than existing BTC-based watermarking schemes, our scheme does not really perform the BTC compression on images during the embedding process but uses the parity of BTC quantization data to guide the watermark embedding and extraction processes. In our scheme, we use a binary image as the original watermark. During the embedding process, the original cover image is first partitioned into non-overlapping $4{\times}4$ blocks. Then, BTC is performed on each block to obtain its BTC quantized high mean and low mean. According to the parity of high mean and the parity of low mean, two watermark bits are embedded in each block by modifying the pixel values in the block to make sure that the parity of high mean and the parity of low mean in the modified block are equal to the two watermark bits. During the extraction process, BTC is first performed on each block to obtain its high mean and low mean. By checking the parity of high mean and the parity of low mean, we can extract the two watermark bits in each block. The experimental results show that the proposed watermarking method is fragile to most image processing operations and various kinds of attacks while preserving the invisibility very well, thus the proposed scheme can be used for image authentication.