A simple and easy to implement technique for improving block truncation coding (BTC) is proposed. The method is based on replacement of bit block obtained using the conventional BTC method with the fuzzy logical bit b...
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A simple and easy to implement technique for improving block truncation coding (BTC) is proposed. The method is based on replacement of bit block obtained using the conventional BTC method with the fuzzy logical bit block (LBB) such that the sample mean and standard deviation in each image block are preserved. This fuzzy LBB is obtained from the fuzzy edge image by using the Yager involutive fuzzy complement edge operator (YIFCEO). The input image is encoded with the block mean and standard deviation and the fuzzy LBB. Experimental results show an improvement of visual quality of reconstructed images and peak signal-to-noise ratio (PSNR) when compared to the conventional BTC. The raggedness and jagged appearance and the ringing artifacts at sharp edges are greatly reduced in the reconstructed images. With the use of YIFCEO, the proposed method is shown to be more flexible to determine the visual quality of the reconstructed images. (C) 2008 Elsevier B.V. All rights reserved.
block truncation coding (BTC) divides an image into blocks having given size and then encodes each block by two representative gray levels and a bit-pattern. In this work a modified scheme of BTC is proposed where the...
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block truncation coding (BTC) divides an image into blocks having given size and then encodes each block by two representative gray levels and a bit-pattern. In this work a modified scheme of BTC is proposed where the computed representative gray levels are the bias and the contrast in each block. Secondly, instead of determining bit-pattern for each block, an optimum bit-pattern is selected from a pattern-book. Thus the index of the optimum pattern is used to encode in lieu of the explicit pattern. Thirdly, if the contrast is low the block is assumed to be smooth and bit-pattern is not required to reconstruct the block. This leads to significant reduction in bit-rate (bpp). Finally, the contrast component and the predictive residual of the bias component are entropy coded to achieve further reduction in bpp. Performance of the proposed scheme is measured in terms of peak-signal-to-noise ratio and bpp, and is compared with other recently reported methods. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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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ISBN:
(纸本)9788388309472
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 gray 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.
In the conventional absolute moment block truncation coding (AMBTC) scheme, the block mean value is taken as the threshold for pixel grouping. But, the use of the block mean value is not optimal in AMBTC subject to th...
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In the conventional absolute moment block truncation coding (AMBTC) scheme, the block mean value is taken as the threshold for pixel grouping. But, the use of the block mean value is not optimal in AMBTC subject to the reconstructed image quality. In this paper, two optimal pixel grouping schemes are put forward for AMBTC. The experimental results shows that the proposed schemes can significantly reduce the computational cost in finding optimal grouping of pixels.
A predictive image compression scheme that combines the advantages of vector quantization and moment preserving block truncation coding is introduced in this paper. To exploit the similarities among neighboring image ...
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A predictive image compression scheme that combines the advantages of vector quantization and moment preserving block truncation coding is introduced in this paper. To exploit the similarities among neighboring image blocks, the block prediction technique is employed in this scheme. If a similar compressed image block can be found in the neighborhood of current processing block, it is taken to encode this block. Otherwise, this image block is encoded either by vector quantization or moment preserving block truncation coding. A bit-rate reduced version of the proposed scheme is also introduced. According to the experimental results, it is shown that the proposed scheme provides better image quality at a low bitrate than these comparative schemes.
Overdriving technique enlarges the desired change of the pixel value, the error in general compression methods is enlarged at the same time. Therefore, we propose a novel Adaptive Quantization coding (AQC) to reduce t...
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ISBN:
(纸本)9783540748724
Overdriving technique enlarges the desired change of the pixel value, the error in general compression methods is enlarged at the same time. Therefore, we propose a novel Adaptive Quantization coding (AQC) to reduce the error in compression for overdriving technique reducing motion blur. Considering hardware implementation, we develop a hybrid image coding which uses color transform first, and then uses AQC to compress luminance data as well as block truncation coding (BTC) to compress chrominance data. The simulation results shown that the average PSNR was improved 5.676dB as compared with the result of BTC, and the average SD of error was reduced 50.2% than that in the BTC. The proposed algorithm is implemented with the verilog HDL and synthesized with the synopsys design compiler using 0.131 mu m Samsung Library.
block truncation coding is an efficient compression technique while offering good image quality. Nonetheless, the blocking effect inherent in BTC causes severe perceptual artifact in high compression ratio application...
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ISBN:
(纸本)9780769530581
block truncation coding is an efficient compression technique while offering good image quality. Nonetheless, the blocking effect inherent in BTC causes severe perceptual artifact in high compression ratio applications. In this paper, an Error-Diffused block truncation coding (EDBTC) is proposed to solve this problem. According to the EDBTC, the error caused by the difference between the original grayscale pixel value and the correspondingly high or low mean substitute is diffused to the predefined neighborhood, and hence the average grayscale will be maintained invariably. In addition, since the compressed data are widely distributed in the internet transmission, the extra message delivering in a secret way also highly raises attention recently. In this paper, we propose the Compressed Steganography using Hidden Referenced Halftoning (CSHRH), which cooperates with error diffusion and ordered dithering to achieve the objective of secret communication in BTC images. As documented in the experimental results, a low complexity with good image quality approach is obtained. Moreover, CSHRH is extended to Secret-Sharing Steganography (SSS) and Color Extension Steganography (CES). The SSS is able to distribute message into multiple host images and hence improves the security. The CES is able to deliver secure message via color embedded CSHRH image. Both extensions are also with an extra benefit of achieving high capacity message convection.
A novel image compression scheme based on absolute moment block truncation coding (AMBTC) is proposed. The quadtree segmentation technique is employed in this scheme to exploit the variable-block-sized segmentation. I...
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A novel image compression scheme based on absolute moment block truncation coding (AMBTC) is proposed. The quadtree segmentation technique is employed in this scheme to exploit the variable-block-sized segmentation. In addition, the concept of using visual patterns to reduce the storage cost of the BTC bit plane is incorporated into this scheme. Finally, the bit plane omission technique is employed if these two quantization levels in each image block are quite similar. According to the experimental results, it is shown that the proposed scheme requires very little computational complexity. Besides, a good image quality of the compressed image can be obtained while the required bit rate is relatively low. In other words, the proposed scheme indeed provides a good approach to compress digital images with little computational cost at a low bit rate. (C) 2003 Society of Photo-Optical Instrumentation Engineers.
In this paper, a novel detection and recovery system is proposed for image authentication based on two compression schemes: block truncation coding and vector quantization. In order to reduce the overhead in the commu...
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In this paper, a novel detection and recovery system is proposed for image authentication based on two compression schemes: block truncation coding and vector quantization. In order to reduce the overhead in the communication, the sender first compresses an image and then refines the characteristic values from the compressed image. The characteristic values are encrypted to digital signatures using the RSA scheme (proposed by Rivest, Shamir and Adleman). The signatures are embedded into the compressed image and thus the image integrity can be authenticated after transmission. Upon receipt of the compressed image, the receiver extracts the signatures and then decrypts the characteristic values using the sender's public key. Another characteristic value can also be decoded by the image compression scheme. By comparing a few characteristic values, the system determines whether or not the decompressed image is tampered and then outputs a correct characteristic value to rebuild the tampered regions. Furthermore, the proposed scheme authenticates the integrity of the image to the receiver and effectively recovers the tampered image.
In this paper, a new edge detection scheme based on block truncation coding (BTC) is proposed. As we know, the BTC is a simple and fast scheme for digital image compression. To detect an edge boundary using the BTC sc...
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In this paper, a new edge detection scheme based on block truncation coding (BTC) is proposed. As we know, the BTC is a simple and fast scheme for digital image compression. To detect an edge boundary using the BTC scheme, the bit plane information of each BTC-compressed block is exploited, and a simple block type classifier is introduced. The experimental results show that the proposed scheme clearly detects the edge boundaries of digital images while requiring very little computational complexity. Meanwhile, the edge detection process can be incorporated into all BTC variant schemes. In other words, the newly proposed scheme provides a good approach for the detection of edge boundaries using block truncation coding.
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