The Experts below are selected from a list of 192 Experts worldwide ranked by ideXlab platform
Chin-chen Chang - One of the best experts on this subject based on the ideXlab platform.
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A Novel Adjustable RDH Method for AMBTC-Compressed Codes Using One-to-Many Map
IEEE Access, 2020Co-Authors: Wenbin Zheng, Chin-chen Chang, Shaowei WengAbstract:Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be deCoded by traditional AMBTC deCoders, because they change the coding structure of the AMBTC Compressed Code stream, which is unidentified for deCoders. Even if some AMBTC-based RDH methods can be deCoded by traditional AMBTC deCoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an $m\times n$ -sized bitmap has $2^{m\times n}$ combinations of ‘1’ and ‘0’. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., $\log _{2} 25$ bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-Compressed Code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.
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A Novel Adjustable RDH Method for AMBTC-Compressed Codes Using One-to-Many Map
IEEE Access, 2020Co-Authors: Wenbin Zheng, Chin-chen Chang, Shaowei WengAbstract:Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be deCoded by traditional AMBTC deCoders, because they change the coding structure of the AMBTC Compressed Code stream, which is unidentified for deCoders. Even if some AMBTC-based RDH methods can be deCoded by traditional AMBTC deCoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an m × n-sized bitmap has 2m×n combinations of `1' and `0'. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., log2 25 bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-Compressed Code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.
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A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity
Symmetry, 2019Co-Authors: Chin-chen Chang, Xu Wang, Ji-hwei HorngAbstract:With the rapid development of smartphones, cloud storage, and wireless communications, protecting the security of Compressed images through data transmission on the Internet has become a critical contemporary issue. A series of data hiding methods for AMBTC Compressed images has been proposed to solve this problem. However, most of these methods either change the file size of the final Compressed Code or exchange the order of two quantization values in some blocks. To reverse this situation, this paper proposes a data hiding method for strict AMBTC format images using a hybrid strategy: replacement, matrix encoding, and symmetric quantization value embedding for three block types i.e., smooth blocks, less complex blocks and highly complex blocks. According to the hybrid strategy, an efficient data hiding order is designed to achieve higher-fidelity. Experimental results show that our proposed method provides an excellent balance between image quality and hiding capacity and has no error blocks in the final stego-Compressed Code.
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A Novel Lossy Image Compression Scheme Based on Hilbert Curve and VQ Suitable for Fast Window Query
2008 Second International Symposium on Intelligent Information Technology Application, 2008Co-Authors: Chin-chen Chang, Ju-yuan HsiaoAbstract:In this paper, a novel lossy image compression scheme suitable for fast window query which is based on Hilbert curve and VQ is proposed. It allows us to perform window query directly on the Compressed Code of a gray-level image without decompressing the full Compressed image first. The compression effect achieved by our method is also excellent. According to the substantial experimental results, the applicability of our method can be demonstrated.
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A Steganographic Method for Hiding Secret Data Using Side Match Vector Quantization
IEICE Transactions on Information and Systems, 2005Co-Authors: Chin-chen Chang, Wen-chuan WuAbstract:To increase the number of the embedded secrets and to improve the quality of the stego-image in the vector quantization (VQ)-based information hiding scheme, in this paper, we present a novel information-hiding scheme to embed secrets into the side match vector quantization (SMVQ) Compressed Code. First, a host image is partitioned into non-overlapping blocks. For these seed blocks of the image, VQ is adopted without hiding secrets. Then, for each of the residual blocks, SMVQ or VQ is employed according to the smoothness of the block such that the proper Codeword is chosen from the state Codebook or the original Codebook to compress it. Finally, these Compressed Codes represent not only the host image but also the secret data. Experimental results show that the performance of the proposed scheme is better than other VQ-based information hiding scheme in terms of the embedding capacity and the image quality. Moreover, in the proposed scheme, the compression rate is better than the compared scheme.
Shaowei Weng - One of the best experts on this subject based on the ideXlab platform.
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A Novel Adjustable RDH Method for AMBTC-Compressed Codes Using One-to-Many Map
IEEE Access, 2020Co-Authors: Wenbin Zheng, Chin-chen Chang, Shaowei WengAbstract:Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be deCoded by traditional AMBTC deCoders, because they change the coding structure of the AMBTC Compressed Code stream, which is unidentified for deCoders. Even if some AMBTC-based RDH methods can be deCoded by traditional AMBTC deCoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an $m\times n$ -sized bitmap has $2^{m\times n}$ combinations of ‘1’ and ‘0’. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., $\log _{2} 25$ bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-Compressed Code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.
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A Novel Adjustable RDH Method for AMBTC-Compressed Codes Using One-to-Many Map
IEEE Access, 2020Co-Authors: Wenbin Zheng, Chin-chen Chang, Shaowei WengAbstract:Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be deCoded by traditional AMBTC deCoders, because they change the coding structure of the AMBTC Compressed Code stream, which is unidentified for deCoders. Even if some AMBTC-based RDH methods can be deCoded by traditional AMBTC deCoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an m × n-sized bitmap has 2m×n combinations of `1' and `0'. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., log2 25 bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-Compressed Code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.
H. Lekatsas - One of the best experts on this subject based on the ideXlab platform.
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Approximate arithmetic coding for bus transition reduction in low power designs
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2005Co-Authors: H. Lekatsas, J. Henkel, W. WolfAbstract:We present a method for reducing the power consumption of Compressed-Code systems by selectively inverting bits that are transmitted on the bus. By incorporating bus inversion into Code compression/decompression, we reduce power consumption with no cost in hardware or power relative to Code compression without inversion. Inverting has to be done carefully to ensure that the Codes can still be deCoded. As an additional challenge, compression will generally increase bit-toggling as it removes redundancies from the Code transmitted. Therefore, we need to find the right balance between compression ratio and bit-toggling reduction. This paper presents a suitable algorithm that will combine approximate compression techniques with bit-toggling reduction and will explore the various tradeoffs. We take advantage of the approximations introduced to modify Codes and reduce bit-toggling, while maintaining compression performance and decoding speed. An interesting result that is derived from our work is that high compression ratios do not necessarily result in the lowest power consumption. By using our method, bus-related power consumption has been reduced by as much as 35% compared to a system with no compression, and as much as 14% compared to a Compressed-Code system. Bit-toggling reduction does not impose any additional hardware costs other than the decompression engine. We also present a detailed analysis on how bus widths affect bit-toggling when transmitting Compressed Code, and we show experimental results on ARM, MIPS, and SPARC Code. We finally compare our work with Bus Invert and show results that are superior except for the random data case where Bus Invert performs better.
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CoCo: a hardware/software platform for rapid prototyping of Code compression technique
Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451), 2003Co-Authors: H. Lekatsas, J. Henkel, S. Chakradhar, V. Jakkula, M. SankaradassAbstract:In recent years, instruction Code compression/decompression technologies have emerged as an efficient way to: a) reduce the memory usage of an embedded system, b) to improve performance through effective higher bandwidths and/or to c) reduce the overall power consumption of a system processing Compressed Code. We have presented efficient Code compression/decompression techniques and architectures in the past. For the commercialization phase, we designed a novel hardware/software Code compression/decompression platform (CoCo). It consists of a software platform that prepares, optimizes, compresses and compiles instruction Code and a generic, parameterizable FPGA-based hardware architecture in form of a hardware platform that allows to rapidly evaluate prototypes of diverse compression/decompression technologies. We show the flexibility of CoCo, its ability to achieve Code compression ratios (parameterizable) of up to 50% with a slight system performance gain and its ability to apply compression in a real-world compiled Code without any limitations where others have made implicit software-restrictive assumptions.
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A decompression architecture for low power embedded systems
Proceedings 2000 International Conference on Computer Design, 2000Co-Authors: H. Lekatsas, J. Henkel, W. WolfAbstract:We present an architecture for embedded systems that decompresses offline-Compressed instructions during runtime. This is useful for Compressed Code systems where instructions are stored in a Compressed format and deCompressed on demand. The result is a significant reduction in power consumption, and in most cases a performance improvement. The stand-alone decompression engine is placed between the instruction cache and the CPU (post-cache architecture) as we have found this to be the most power-efficient architecture. This paper describes the design of this unit in detail and analyzes its power consumption and performance.
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Code compression for embedded systems
Proceedings 1998 Design and Automation Conference. 35th DAC. (Cat. No.98CH36175), 1998Co-Authors: H. Lekatsas, W. WolfAbstract:Memory is one of the most restricted resources in many modern embedded systems. Code compression can provide substantial savings in terms of size. In a Compressed Code CPU, a cache miss triggers the decompression of a main memory block, before it gets transferred to the cache. Because the Code must be decompressible starting from any point (or at least at cache block boundaries), most file-oriented compression techniques cannot be used. We propose two algorithms to compress Code in a space-efficient and simple to decompress way, one which is independent of the instruction set and another which depends on the instruction set. We perform experiments on true instruction sets, a typical RISC (MIPS) and a typical CISC (x86) and compare our results to existing file-oriented compression algorithms.
Benoit Macq - One of the best experts on this subject based on the ideXlab platform.
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Scalable Feature Extraction for Coarse-to-Fine JPEG 2000 Image Classification
IEEE Transactions on Image Processing, 2011Co-Authors: Antonin Descampe, Christophe De Vleeschouwer, Pierre Vandergheynst, Benoit MacqAbstract:In this paper, we address the issues of analyzing and classifying JPEG 2000 Code-streams. An original representation, called integral volume, is first proposed to compute local image features progressively from the Compressed Code-stream, on any spatial image area, regardless of the Code-blocks borders. Then, a JPEG 2000 classifier is presented that uses integral volumes to learn an ensemble of randomized trees. Several classification tasks are performed on various JPEG 2000 image databases and results are in the same range as the ones obtained in the literature with nonCompressed versions of these databases. Finally, a cascade of such classifiers is considered, in order to specifically address the image retrieval issue, i.e., bi-class problems characterized by a highly skewed distribution. An efficient way to learn and optimize such cascade is proposed. We show that staying in a JPEG 2000 framework, initially seen as a constraint to avoid heavy decoding operations, is actually an advantage as it can benefit from the multiresolution and multilayer paradigms inherently present in this compression standard. In particular, unlike other existing cascaded retrieval systems, the features used along our cascade are increasingly discriminant and lead therefore to a better tradeoff of complexity versus performance.
Prabhat Mishra - One of the best experts on this subject based on the ideXlab platform.
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VLSI Design - Efficient Placement of Compressed Code for Parallel Decompression
2009 22nd International Conference on VLSI Design, 2009Co-Authors: Prabhat MishraAbstract:Code compression is important in embedded systems design since it reduces the Code size (memory requirement) and thereby improves overall area, power and performance. Existing researches in this field have explored two directions: efficient compression with slow decompression, or fast decompression at the cost of compression efficiency. This paper combines the advantages of both approaches by introducing a novel bitstream placement method. The contribution of this paper is a novel Code placement technique to enable parallel decompression without sacrificing the compression efficiency. The proposed technique splits a single bitstream (instruction binary) fetched from memory into multiple bitstreams, which are then fed into different deCoders. As a result, multiple slow-deCoders can work simultaneously to produce the effect of high deCode bandwidth. Our experimental results demonstrate that our approach can improve deCode bandwidth up to four times with minor impact (less than 1%) on compression efficiency.
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Efficient Placement of Compressed Code for Parallel Decompression
2009 22nd International Conference on VLSI Design, 2009Co-Authors: Prabhat MishraAbstract:Code compression is important in embedded systems design since it reduces the Code size (memory requirement) and thereby improves overall area, power and performance. Existing researches in this field have explored two directions: efficient compression with slow decompression, or fast decompression at the cost of compression efficiency. This paper combines the advantages of both approaches by introducing a novel bitstream placement method. The contribution of this paper is a novel Code placement technique to enable parallel decompression without sacrificing the compression efficiency. The proposed technique splits a single bitstream (instruction binary) fetched from memory into multiple bitstreams, which are then fed into different deCoders. As a result, multiple slow-deCoders can work simultaneously to produce the effect of high deCode bandwidth. Our experimental results demonstrate that our approach can improve deCode bandwidth up to four times with minor impact (less than 1%) on compression efficiency.