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Energy efficient novel architectures for the lifting-based discrete wavelet transform

IET image PROCESSING 2007年第3期1卷 305-310页

作者： Varshney, H. Hasan, M. Jain, S. Aligarh Muslim Univ Dept Elect Engn Aligarh Uttar Pradesh India

Energy efficient single-processor and fully pipelined architectures for the lifting-based JPEG2000's 5/3 two-dimensional (2D)-discrete wavelet transform are presented. The single processor performs both the row- and column-wise processing simultaneously, that is, full 2D transform with 100% hardware utilisation. In addition, the architecture uses minimum embedded memory. The fully pipelined architecture is obtained by replicating the single-processor block depending on the levels of decomposition with much lower memory requirement and higher throughput than the single processor involved in multi-level transforms. These architectures can be directly used in real-time image/video consumer applications to extend the battery life of portable systems.

关键词： pipeline processing Parallel architecture energy efficient single-processor Memory circuits discrete wavelet transforms Computer vision and image processing techniques image and video coding image coding lifting-based JPEG2000 2D discrete wavelet transform pipelined architecture embedded memory real-time image-video consumer application Integral transforms Storage system design memory architecture

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Digital image steganalysis: A survey on paradigm shift from machine learning to deep learning based techniques

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IET image PROCESSING 2021年第2期15卷 504-522页

作者： Selvaraj, Arivazhagan Ezhilarasan, Amrutha Wellington, Sylvia Lilly Jebarani Sam, Ananthi Roy Mepco Schlenk Engn Coll Autonomous Ctr Image Proc & Pattern Recognit Dept Elect & Commun Engn Sivakasi 626005 Tamil Nadu India

Steganography, a branch of data hiding techniques aims to hide confidential information within any digital media by obscuring the existence of hidden information. On the contrary, steganalysis aims to detect steganography. With the advent of powerful steganographic algorithms, the process of cracking them became very challenging. Traditional steganalysis following machine learning principle employs a two-step process, with first process extracting highly sophisticated features capable of discriminating hidden message from original data and second process classifying the input as innocent or guilty. In recent years, deep learning which has its roots in artificial neural networks emerged as a brilliant alternative for many computer vision tasks. A review of recent research works in deep learning based digital image steganalysis is presented here. The paradigm shift from machine learning approaches to employing more promising deep learning architectures, observed with the current research community and hence in literature has been presented here in chronological order. Deep learning can unify the two-step process into a single process by giving the ability for machine to learn end-to-end by itself. The use of Convolutional Neural Networks to perform steganalysis in spatial or transform or combination of both domains has effectively lowered the detection error rates.

关键词： Cryptography Optical, image and video signal processing image and video coding Computer vision and image processing techniques Data security Other topics in statistics

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Error resilient video coding with priority data classification using H.264 flexible macroblock ordering

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IET image PROCESSING 2007年第2期1卷 197-204页

作者： Im, S. K. Pearmain, A. J. Univ London Queen Mary Coll Dept Elect Engn London E1 4NS England

Flexible macroblock ordering (FMO) is a new error resilience feature in the H.264 (MPEG-4 part 10) video coding standard. The paper exploits FMO to offer a new classification algorithm for prioritised video transmission. Instead of using the default mapping structures of FMO, an optimisation algorithm in which the more important macroblocks (MBs) are categorised in a separate slice group (SG), which corresponds to high-priority packets for transmission, is proposed. The importance of each MB is determined based on its eventual influence on picture quality. This is assessed by considering the fact that the successful transmission of an MB not only enhances the quality of the associated pixels, but also improves the quality of its adjacent lost MBs by improving the efficiency of error concealment. It is assumed that the network can offer a prioritised service for successful transmission of the high-priority SG. Based on this, a vulnerability factor for each MB is determined, and a certain proportion of high-vulnerability MBs at each frame to limit the impact of temporal error propagation is intra-updated. It is shown, where the proposed mapping algorithm outperforms the default mappings of the H.264 codec, that this prioritised transmission will improve the subjective and objective video quality in situations with a high probability of transmission errors.

关键词： prioritised video transmission priority data classification mapping algorithm H.264 flexible macroblock ordering FMO Computer vision and image processing techniques image and video coding error propagation video coding optimisation algorithm image classification video coding standard picture quality video signal processing MPEG-4 part 10 slice group error resilient video coding vulnerability factor codec

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Closure of sets: a statistically hypersensitive system for steganalysis of least significant bit embedding

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IET SIGNAL PROCESSING 2011年第4期5卷 379-389页

作者： Khosravirad, S. R. Eghlidos, T. Ghaemmaghami, S. Sharif Univ Technol Elect Res Inst Tehran Iran

This study introduces a new scheme for steganalysis of the least significant bit (LSB) embedding, based on the idea of closure of sets (CoS), which is independent of the type of cover signal, applicable to both spatial and transform domains. The CoS is referred to as some special subsets that could be found in a common space whose elements relate to higher-order statistical properties of the signal. The proposed scheme is used for steganalysis of the LSB steganography of greyscale TIFF and JPEG images and audio signals, employing a set of accurate and monotone features that are extracted based on the CoS definition. It is shown that significant improvement to the detection accuracy in steganalysis is achieved using the proposed scheme, particularly at low embedding rates.

关键词： Computer vision and image processing techniques closure of sets Data security image and video coding steganography image coding Cryptography least significant bit embedding statistically hypersensitive system steganalysis feature extraction transforms spatial domain audio signals Speech and audio coding JPEG images audio coding transform domain greyscale TIFF images image colour analysis least significant bit steganography Integral transforms monotone feature extraction higher-order statistical property

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Security augmentation grounded on Fresnel and Arnold transforms using hybrid chaotic structured phase mask

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IET image PROCESSING 2021年第5期15卷 1042-1052页

作者： Yadav, Shivani Singh, Hukum NorthCap Univ Dept Appl Sci Sect 23-A Gurugram India

A novel asymmetric double image encryption technique is introduced to protect the algorithm from the interlopers by using hybrid chaotic structured phase masks in Arnold and Fresnel transforms. Mostly random phase masks are used routinely in many algorithms which are not strong against many attacks. So, taking in consideration replacing of random phase masks with the new hybrid chaotic structured phase masks takes place in the algorithm. With the assistance of Fresnel zone plates, radial Hilbert mask and logistic map functions, the chaotic structured phase mask is accumulated and hybrid chaotic structured phase mask provides extra security to system. Arnold transform helps in pixel shuffling, and with the pixel reorganization, it also helps in image reaping and bordering. The propagation distance of the Fresnel transform and the constraints of the Arnold transform serve as keys for encryption and decryption. To check the sturdiness of hybrid chaotic structured phase mask, simulations have been done which are carried out by the support of MATLAB R2018a (9.4.0.813654).

关键词： Cryptography image and video coding Integral transforms in numerical analysis Computer vision and image processing techniques Data security Integral transforms in numerical analysis

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Histogram ordering model-based fast motion estimation

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IET image PROCESSING 2012年第3期6卷 238-250页

作者： Park, S. -J. Hong, S. -M. Lee, H. Jin, S. Jeong, J. Hanyang Univ Dept Elect & Comp Engn Seoul 133791 South Korea Hanyang Univ Dept Intelligent Robot Seoul 133791 South Korea LG Elect Inc SIC Ctr DTVSoC Dept SAT Gr Seoul South Korea

This study proposes two efficient block matching algorithms for fast motion estimation using a histogram ordering model in order to reduce the computational cost of video coding. Since the representative pixels that consist of edge or texture mainly contribute to the block matching criterion, it is important to analyse the details of the current block. To analyse the characteristics of the block with low complexity, the pixel histogram is used for the observation of the block. Based on this pixel histogram for the current block, an optimal block matching order is determined for the lossless fast matching algorithm. In addition, adaptive partial block matching algorithm for lossy fast motion estimation using histogram-based block matching ordering is also presented to further reduce the complexity of block matching. By capturing the representative pixels, block matching distortion is maximised soon enough during the block matching. For this reason, partial block matching is available instead of full block matching, which is also known as a full search algorithm. Our experimental results show that the proposed algorithm not only reduces the computational complexity of block matching criterion, but also tends to maintain the image quality when compared to the conventional fast matching algorithms.

关键词： search problems image quality fast motion estimation Optimisation techniques partial block matching histogram-based block matching ordering model image and video coding motion estimation pixel histogram full search algorithm block matching algorithms image matching video coding representative pixels block matching criterion image texture Computational complexity video signal processing block matching distortion computational complexity optimal block matching order computational cost reduction Combinatorial mathematics block matching complexity

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Dynamic threshold-based keyframe detection and its application in rate control

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IET image PROCESSING 2012年第7期6卷 986-995页

作者： Yao, W. Li, Z. Rahardja, S. Inst Infocomm Res Signal Proc Dept Singapore Singapore

This study proposes a new dynamic threshold model to detect keyframes for the coding of a video sequence. The proposed detection threshold is content adaptive which dynamically updates its value at each frame by taking into consideration both the statistical properties of the video sequence and the resolution as well as the quantisation parameters. The content variation metric used in the proposed detection method utilises the information that is already generated by the encoder during the encoding process and thus it makes the detection process fast. By applying the proposed scheme to rate control, the sizes of group of pictures are now adapted to the video content and it removes the temporal redundancy among different frames better, which transforms to the improvements on coding efficiency. The experimental results have shown that the proposed method achieves peak signal-to-noise ratio (PSNR) improvement.

关键词： image resolution statistical analysis temporal redundancy encoding process dynamic threshold model dynamic threshold-based keyframe detection coding efficiency image and video coding rate control quantisation parameters quantisation (signal) encoder video coding image sequences peak signal-to-noise video resolution video signal processing detection process content variation metric statistical properties video sequence coding PSNR Other topics in statistics

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A screen-shooting resilient document image watermarking scheme using deep neural network

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IET image PROCESSING 2023年第2期17卷 323-336页

作者： Ge, Sulong Fei, Jianwei Xia, Zhihua Tong, Yao Weng, Jian Liu, Jianan Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Nanjing Univ Informat Sci & Technol Engn Res Ctr Digital Forens Nanjing Peoples R China Jinan Univ Coll Cyber Secur Guangzhou Peoples R China Guangzhou Fongwell Data Ltd Co Guangzhou Peoples R China

With the advent of the screen-reading era, the confidential documents displayed on the screen can be easily captured by a camera without leaving any traces. Thus, this paper proposes a novel screen-shooting resilient watermarking scheme for document image using deep neural network. By applying this scheme, when the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the captured photographs. Specifically, the scheme is an end-to-end neural network with an encoder to embed watermark and a decoder to extract watermark. During the training process, a distortion layer between encoder and decoder is added to simulate the distortions introduced by screen-shooting process in real scenes, such as camera distortion, shooting distortion, and light source distortion. Furthermore, a background sensitive loss and a lpips loss are used to improve visual quality of the watermarked document images in the training process. Besides, a strength factor adjustment strategy is also designed to improve the visual quality with little loss of bit extraction accuracy. The experimental results show that the proposed scheme has higher visual quality and robustness than the other two recent state-of-the-art methods.

关键词： feature extraction shooting distortion background sensitive loss camera distortion screen-shooting resilient document image watermarking distortion layer Document processing and analysis techniques image and video coding bit extraction Neural nets image watermarking Computer vision and image processing techniques strength factor adjustment end-to-end neural network confidential documents deep learning (artificial intelligence) document image processing Data security deep neural network watermark extraction lpips loss light source distortion screen-reading era visual quality

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Efficient algorithm for very low bit rate embedded image coding

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IET image PROCESSING 2008年第2期2卷 59-71页

作者： Moinuddin, A. A. Khan, E. Ghanbari, M. Aligarh Muslim Univ Dept Elect Engn Aligarh Uttar Pradesh India Univ Essex Dept Comp & Elect Syst Colchester CO4 3SQ Essex England

The authors propose an embedded wavelet-based image coding algorithm that exploits both the inter- and intra-subband correlations among the wavelet coefficients. The proposed coding algorithm is based on spatial orientation trees (SOT) in which the basic unit is a block of m x n coefficients in contrast to a single coefficient in the set partitioning in hierarchical trees (SPIHT) algorithm. Each SOT has a root node (a block of m x n coefficients) in the LL-subband with the child and descendent blocks in the high frequency subbands. Thus it fuses the features of both block- and tree-based coding algorithms into a single algorithm. Performance of the proposed method is compared (in terms of rate-distortion performance) with the other state-of-the-art coding algorithms including the JPEG2000 for popular test images. Simulation results show that the proposed algorithm has a better coding efficiency over the other coders at very low bit rates. Also, compared with SPIHT it reduces the elements of the auxiliary lists, thereby reducing the memory requirements. In addition, the encoder of the proposed algorithm is significantly faster than that of the SPIHT, but with a slight increase in its decoder complexity.

关键词： low bit rate embedded image coding set partitioning Computer vision and image processing techniques data encapsulation image and video coding image coding wavelet transforms hierarchical tree algorithm Combinatorial mathematics Integral transforms spatial orientation tree decoding trees (mathematics)

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Linking run-time resource management of embedded multi-core platforms with automated design-time exploration

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IET COMPUTERS AND DIGITAL TECHNIQUES 2011年第2期5卷 123-135页

作者： Ykman-Couvreur, C. Avasare, P. Mariani, G. Palermo, G. Silvano, C. Zaccaria, V. IMEC VZW IBBT B-3001 Louvain Belgium Univ Lugano ALaRI Lugano Switzerland Politecn Milan Dipartimento Elect & Informaz Milan Italy

Nowadays, owing to unpredictable changes of the environment and workload variation, optimally running multiple applications in terms of quality, performance and power consumption on embedded multi-core platforms is a huge challenge. A lightweight run-time manager, linked with an automated design-time exploration and incorporated in the host processor of the platform, is required to dynamically and efficiently configure the applications according to the available platform resources (e. g. processing elements, memories, communication bandwidth), for minimising the cost (e. g. power consumption), while satisfying the constraints (e. g. deadlines). This study presents a flow linking a design-time design space explorer, coupled with platform simulators at two abstraction levels, with a fast and lightweight priority-based heuristic integrated in the run-time manager to select near-optimal application configurations. To illustrate its feasibility and the very low complexity of the run-time selection, the proposed flow is used to manage the processors and clock frequencies of a multiple-stream MPEG4 encoder chip dedicated to automotive cognitive safety applications.

关键词： priority-based heuristic video coding video signal processing Microprocessor chips Multiprocessing systems image and video coding Civil and mechanical engineering computing design-time design space explorer Digital signal processing chips Microprocessors and microcomputers run-time manager automotive engineering run-time resource management host processor platform simulators digital signal processing chips run-time selection automotive cognitive safety automated design-time exploration MPEG4 encoder chip embedded multicore platform road safety resource allocation multiprocessing systems

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