• 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.

• 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 Information and Telecommunication Facilities Engineering
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• v.10 no.2
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• pp.80-85
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• 2011

In this paper, I propose flexible base point used for a BTC(Block Truncation Coding). Halftoning images are used for printer by reducing the number of pixel depth. During over 20 years, many researches have been studied to apply this techniques to image compression. BTC algorithms are the compression methods using digital halftoning technique about images. In the BTC algorithm, an image block is divided into higher and lower domain compared with the mean of block. then the MAX and MIN representative values are evaluated by calculating the mean of higher and lower domain respectively. At a result, an image block(for example 88 size) is compressed into 64bits pixel representation and 16 bits of the MAX and MIN. And they also have been tried to sustain the image quality high after compression. In this paper, I found that there is some marginal possibility to enhance the image quality by adjusting the base point(generally mean of block) of existing algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.27-34
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• 2009

Block truncation coding (BTC) is a simple and efficient image compression technique. However, it yields images of unacceptable quality and significant blocking effects are seen when the block size is increasing. Ordered dither block truncation coding (ODBTC) was proposed to solve above problem maintaining the same compression capability. In this paper, we propose a data hiding method which can be applied to halftone images. EMD was developed by Zhang and Wang [6] for data hiding in the grayscale image. Therefore, EMD is not proper for bitmap images. In this paper, we show that EMD can be used to apply bitmap halftone image. In our experiments, we prove that our method is efficient in a halftone image.

• 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.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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.73-86
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• 1993

This paper proposes an automatic variable block truncation coding (BTC) method. It selects the block size automatically based on the mode of the discontinutiy measure of blocks. The combination of an automatic block-size determination scheme and the conventional BTC results in the proposed automatic variable BTC techniques. For color images, subsampling in I and Q chrominance components is adopted along with the variable BTC. To show the effectiveness of the proposed algorithm, its simulation results are compared to those of the several conventional BTC algorithms for monochrome and color test images. Computer simulation shows that the proposed algorithm gives better performance than the conventional ones based on the subjective and objective performance evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2326-2345
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• 2016

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.125-131
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• 1989

This paper proposes a new ABTC (Adaptive Block Truncation Coding) algorithm which improves the BTC algorithm for image data compression. A new adaptive block truncation coding which adopts a selective coding scheme depending on the local characteristics of an image has been described. The characteristics of the ABTC algorithm can be summarized as high compression ratio and the algorithm simplicity. Using this algorithm, color images can be coded at a variable bit rate from 1.0 (bit/pel) to 2.56 (bit/pel) and high compression rate (1.3-105 bit/pel) can be achieved without conspicuous image degradation compared with original images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1546-1552
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• 1993

We proposed an adaptive block truncation coding(BTC) using gradient and a new initial value. We used gradient of sobel operator as a new category classification coefficient to reduce Jagged appearance at edge part. We defined a new initial value to reduce large quantization error in the 4-level quantizer block including edge part. By computer simulations, we showed that the proposed method less computation load, reduced jagged appearance at edge part, also improved PSNR more than the conventional adaptive BTC.