A novel image authentication scheme which can protect the image integrity of the compressed images for block truncation coding (BTC) is proposed in this paper. In the proposed scheme, the authentication codes are embe...
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A novel image authentication scheme which can protect the image integrity of the compressed images for block truncation coding (BTC) is proposed in this paper. In the proposed scheme, the authentication codes are embedded into the the quatization levels of each BTC-compressed image block by using reference matrix- RM (B) . The size of the authentication codes can be decided according to the user's requirement by adjusting the value of B in Reference Matrix. The experimental results demonstrate that the proposed method outperforms previous approaches in image quality of the embedded image and high detecting accuracy.
In this paper, an algorithm for digital image watermarking based on discrete wavelet transforms ( DWT) and block truncation coding ( BTC) has been proposed. In the embedding process, the host image is decomposed into ...
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In this paper, an algorithm for digital image watermarking based on discrete wavelet transforms ( DWT) and block truncation coding ( BTC) has been proposed. In the embedding process, the host image is decomposed into first level DWT and the watermark image is compressed by BTC. The compressed watermark is then embedded into the selected sub-band of the host image. The proposed method has been extensively tested against numerous known signal processing attacks and has been found to be robust and highly imperceptible. Further, the performance of the algorithm has been tested with fractal compression technique. The performance of the BTC-based technique is better than the fractal-based compression techniques in terms of robustness and imperceptibility.
block truncation coding (BTC) is an efficient compression technique for its inherent simple coding strategy. However, the annoying blocking effect and false contour accompanied in high coding gain configurations make ...
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block truncation coding (BTC) is an efficient compression technique for its inherent simple coding strategy. However, the annoying blocking effect and false contour accompanied in high coding gain configurations make the applications relatively limited compares to some up-to-date compression schemes. For this, Error-Diffused block truncation coding (EDBTC) is proposed to solve these problems and obtain satisfactory results. Unfortunately, the EDBTC sacrifices the parallel advantage of traditional BTC. Moreover, the number of diffused directions of EDBTC can be reduced to obtain higher efficiency. For these, the Interlaced Error-Diffused block truncation coding (IEDBTC) is proposed in this work to claim back the parallel advantage. In addition, the diffused elements are also reduced from four to two with the proposed optimization procedure while preserving the image quality.
To reduce frame memory usage in LCD overdrive, block truncation coding (BTC) is commonly used due to its efficient coding and low implementation cost. However, the inherent limitation of BTC causes severe perceptual a...
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To reduce frame memory usage in LCD overdrive, block truncation coding (BTC) is commonly used due to its efficient coding and low implementation cost. However, the inherent limitation of BTC causes severe perceptual artifacts and degrades overdrive performance. To solve this problem, we propose an adaptive multi-level BTC (AM-BTC) in this paper. The AM-BTC firstly overcomes the limitation by adaptively selecting 2-level or 4-level BTC according to the edge property of the codingblock. Then, to reduce the bit rate of AM-BTC we improve the 2-level and 4-level BTCs by using only luminance bit-map to represent three color bit-maps. As shown in simulation results, the AM-BTC successfully reduces the frame memory usage to 1/6 and significantly improves coding performance (up to 3.779 dB) as compared with other algorithms. When the AM-BTC is applied to LCD overdrive, it also improves overdrive performance up to 3.390 dB as compared with other competitive methods in literature(1).
This paper presents an information hiding method in the BTC-compressed domain based on histogram modification and visual cryptography. By using the visual cryptography algorithm, the secret image is divided into sever...
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This paper presents an information hiding method in the BTC-compressed domain based on histogram modification and visual cryptography. By using the visual cryptography algorithm, the secret image is divided into several transparencies, which are called shared images. Then, one shared image is embedded into the BTC-compressed data through histogram modification which is a reversible information hiding algorithm. When there is any need to recover the secret image, the shared image which formerly embedded into the BTC-compressed data can be extracted. Stacking the embedded shared image and the shared image we have already known, the secret image can be recovered. Experimental results demonstrate the feasibility of the proposed method, and the tampering location ability is quite good.
block truncation coding (BTC) has been considered as a highly efficient compression technique for decades. However, the annoying blocking effect and false contour under low bit rate configuration are its key problems....
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ISBN:
(纸本)9781424453092
block truncation coding (BTC) has been considered as a highly efficient compression technique for decades. However, the annoying blocking effect and false contour under low bit rate configuration are its key problems. In this work, an improved BTC, namely Dot-Diffused BTC (DDBTC), is proposed to solve these problems. On one hand, the DDBTC can provide excellent processing efficiency by exploiting the innate parallelism advantage of dot diffusion. On the other hand, the DDBTC can provide excellent image quality by co-optimizing the class matrix and diffused matrix of the dot diffusion. The experimental results demonstrate that the proposed DDBTC is fully superior to the pervious Error-Diffused BTC (EDBTC) in terms of image quality and processing efficiency, and has much better image quality than that of the Ordered-Dither BTC (ODBTC).
A novel removable visible watermarking (RVW) algorithm by combining block truncation coding (BTC) and chaotic map (RVWBCM) is presented in this paper. It embeds a visible watermark in the BTC codes of images, namely b...
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A novel removable visible watermarking (RVW) algorithm by combining block truncation coding (BTC) and chaotic map (RVWBCM) is presented in this paper. It embeds a visible watermark in the BTC codes of images, namely both the host image and the watermarked image are BTC compressed images. First, the original image is divided into watermarked region and non-watermarked region, and a predicted version of original image can be obtained by predicting pixel values in watermarked region. Second, adaptive embedding factors are computed according to the image features. Third, the watermark is adaptively embedded into two quantization levels of the BTC compressed image in visible manner. Meanwhile, to further prevent illegal watermark removal, original bi-level watermark is encrypted and then losslessly embedded in invisible manner by adjusting the relationship of two quantization levels. At the receiver's end, only authorized users can exactly extract original bi-level watermark according the relationship of two quantization levels of BTC codes and succeed in remove the embedded visible watermark to reconstruct the original image. The experimental results show that this scheme can achieve a good balance between perceptual transparence and the watermark strength (watermark visibility) and can resist common image processing attacks. The proposed algorithm has low complexity and simplicity of implementation due to the use of BTC. It can be applicable to copyright notification and secure access control in mobile communication.
Data hiding encompasses a wide range of applications for embedding messages in content. However, hiding data inevitably destroys the host image, even though the distortion is imperceptible. To enhance the hiding capac...
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Data hiding encompasses a wide range of applications for embedding messages in content. However, hiding data inevitably destroys the host image, even though the distortion is imperceptible. To enhance the hiding capacity and maintain the quality of the host image after embedding hidden data, in this paper, we present a high payload reversible data hiding scheme that is based on the absolute moment block truncation coding (AMBTC) compression domain. We explore the redundancy in a block of AMBTC-compressed images to determine if a block is embeddable or non-embeddable. Next, we create four disjoint sets for embeddable blocks to embed data using different combinations of the mean value and the standard deviation. Performance comparisons with other BTC-based schemes are provided to demonstrate the superiority of the proposed scheme.
block truncation coding (BTC) is one of spatial coding techniques of images. This technique has a simple and fast algorithm which achieves constant bit rate of 2 bits per pixel. The compression ratio may be improved b...
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block truncation coding (BTC) is one of spatial coding techniques of images. This technique has a simple and fast algorithm which achieves constant bit rate of 2 bits per pixel. The compression ratio may be improved by coding only half of the bits in the BTC bit plane of each block;the other half will be interpolated at the receiver. The resulting bit rate will be 1.5 bits per pixel. In this paper, two proposed interpolative algorithms for coding the block truncated image bit plane are presented. Several grey scale test images are used to evaluate the coding efficiency and performance of these algorithms compared with existing algorithms. It is generally shown that the proposed algorithms give better results.
block truncation coding (BTC) is an efficient image compression algorithm that generates a constant output bit-rate. For color image compression, vector quantization (VQ) is exploited to improve the coding efficiency....
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block truncation coding (BTC) is an efficient image compression algorithm that generates a constant output bit-rate. For color image compression, vector quantization (VQ) is exploited to improve the coding efficiency. In this letter, we propose ail improved VQ based BTC (VQ-BTC) algorithm using template matching and Lloyd quantization (LQ). The experimental results show that the proposed method improves the PSNR by 0.9 dB in average compared to the conventional VQ-BTC algorithms.
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