As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by havin...As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.展开更多
Based on the ideas of controlling relative quality and rearranging bitplanes, a new ROI coding method for JPEG2000 was proposed, which shifts and rearranges bitplanes in units of bitplane groups. It can code arbitrary...Based on the ideas of controlling relative quality and rearranging bitplanes, a new ROI coding method for JPEG2000 was proposed, which shifts and rearranges bitplanes in units of bitplane groups. It can code arbitrary shaped ROI without shape coding, and reserve almost arbitrary percent of background information. It also can control the relative quality of progressive decoded images. In addition, it is easy to be implemented and has low computational cost.展开更多
To compress hyperspectral images, a low complexity discrete cosine transform （DCT）-based distributed source coding （DSC） scheme with Gray code is proposed. Unlike most of the existing DSC schemes, which utilize tr...To compress hyperspectral images, a low complexity discrete cosine transform （DCT）-based distributed source coding （DSC） scheme with Gray code is proposed. Unlike most of the existing DSC schemes, which utilize transform in spatial domain, the proposed algorithm applies transform in spectral domain. Set-partitioning-based approach is applied to reorganize DCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. The extracted refinement bits are Gray encoded. Because of the dependency along the line dimension of hyperspectral images, low density paritycheck-（LDPC）-based Slepian-Wolf coder is adopted to implement the DSC strategy. Experimental results on airborne visible/infrared imaging spectrometer （AVIRIS） dataset show that the proposed paradigm achieves up to 6 dB improvement over DSC-based coders which apply transform in spatial domain, with significantly reduced computational complexity and memory storage.展开更多
In recent years,with the massive growth of image data,how to match the image required by users quickly and efficiently becomes a challenge.Compared with single-view feature,multi-view feature is more accurate to descr...In recent years,with the massive growth of image data,how to match the image required by users quickly and efficiently becomes a challenge.Compared with single-view feature,multi-view feature is more accurate to describe image information.The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval.In this paper,a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed.By learning the data correlation between different views,this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval results.This algorithm uses a quantitative hash method to generate binary sequences,and uses the hash code generated by the association features to construct database inverted index files,so as to reduce the memory burden and promote the efficient matching.In order to reduce the matching error of hash code and ensure the retrieval accuracy,this algorithm uses inverted multi-index structure instead of single-index structure.Compared with other advanced image retrieval method,this method has better retrieval performance.展开更多
Traditional three-dimensional(3D)image reconstruction method,which highly dependent on the environment and has poor reconstruction effect,is easy to lead to mismatch and poor real-time performance.The accuracy of feat...Traditional three-dimensional(3D)image reconstruction method,which highly dependent on the environment and has poor reconstruction effect,is easy to lead to mismatch and poor real-time performance.The accuracy of feature extraction from multiple images affects the reliability and real-time performance of 3D reconstruction technology.To solve the problem,a multi-view image 3D reconstruction algorithm based on self-encoding convolutional neural network is proposed in this paper.The algorithm first extracts the feature information of multiple two-dimensional(2D)images based on scale and rotation invariance parameters of Scale-invariant feature transform(SIFT)operator.Secondly,self-encoding learning neural network is introduced into the feature refinement process to take full advantage of its feature extraction ability.Then,Fish-Net is used to replace the U-Net structure inside the self-encoding network to improve gradient propagation between U-Net structures,and Generative Adversarial Networks(GAN)loss function is used to replace mean square error(MSE)to better express image features,discarding useless features to obtain effective image features.Finally,an incremental structure from motion(SFM)algorithm is performed to calculate rotation matrix and translation vector of the camera,and the feature points are triangulated to obtain a sparse spatial point cloud,and meshlab software is used to display the results.Simulation experiments show that compared with the traditional method,the image feature extraction method proposed in this paper can significantly improve the rendering effect of 3D point cloud,with an accuracy rate of 92.5%and a reconstruction complete rate of 83.6%.展开更多
A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inne...A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.展开更多
This paper presents an efficient quadtree based fractal image coding scheme in wavelet transform domain based on the wavelet based theory of fractal image compression introduced by Davis. In the scheme, zerotrees of...This paper presents an efficient quadtree based fractal image coding scheme in wavelet transform domain based on the wavelet based theory of fractal image compression introduced by Davis. In the scheme, zerotrees of wavelet coefficients are used to reduce the number of domain blocks, which leads to lower bit cost required to represent the location information of fractal coding, and overall entropy constrained optimization is performed for the decision trees as well as for the sets of scalar quantizers and self quantizers of wavelet subtrees. Experiment results show that at the low bit rates, the proposed scheme gives about 1 dB improvement in PSNR over the reported results.展开更多
A modular architecture for two dimension (2 D) discrete wavelet transform (DWT) is designed.The image data can be wavelet transformed in real time,and the structure can be easily scaled up to higher levels of DWT.A f...A modular architecture for two dimension (2 D) discrete wavelet transform (DWT) is designed.The image data can be wavelet transformed in real time,and the structure can be easily scaled up to higher levels of DWT.A fast zerotree image coding (FZIC) algorithm is proposed by using a simple sequential scan order and two flag maps.The VLSI structure for FZIC is then presented.By combining 2 D DWT and FZIC,a wavelet image coder is finally designed.The coder is programmed,simulated,synthesized,and successfully verified by ALTERA CPLD.展开更多
Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborh...Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.展开更多
Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used ...Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used as the initial value of the chaotic system. Second, the chaotic sequence and Fisher–Yatess scrambling are used to scramble the plaintext,and a sorting scrambling algorithm is used for secondary scrambling. Then, the chaotic sequence and DNA coding rules are used to change the plaintext pixel values, which makes the ciphertext more random and resistant to attacks, and thus ensures that the encrypted ciphertext is more secure. Finally, we add plaintext statistics for pixel-level diffusion to ensure plaintext sensitivity. The experimental results and security analysis show that the new algorithm has a good encryption effect and speed, and can also resist common attacks.展开更多
A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. ...A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.展开更多
In the sorting system of the production line,the object movement,fixed angle of view,light intensity and other reasons lead to obscure blurred images.It results in bar code recognition rate being low and real time bei...In the sorting system of the production line,the object movement,fixed angle of view,light intensity and other reasons lead to obscure blurred images.It results in bar code recognition rate being low and real time being poor.Aiming at the above problems,a progressive bar code compressed recognition algorithm is proposed.First,assuming that the source image is not tilted,use the direct recognition method to quickly identify the compressed source image.Failure indicates that the compression ratio is improper or the image is skewed.Then,the source image is enhanced to identify the source image directly.Finally,the inclination of the compressed image is detected by the barcode region recognition method and the source image is corrected to locate the barcode information in the barcode region recognition image.The results of multitype image experiments show that the proposed method is improved by 5+times computational efficiency compared with the former methods,and can recognize fuzzy images better.展开更多
Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Seco...Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.展开更多
In this paper, we propose a sparse overcomplete image approximation method based on the ideas of overcomplete log-Gabor wavelet, mean shift and energy concentration. The proposed approximation method selects the neces...In this paper, we propose a sparse overcomplete image approximation method based on the ideas of overcomplete log-Gabor wavelet, mean shift and energy concentration. The proposed approximation method selects the necessary wavelet coefficients with a mean shift based algorithm, and concentrates energy on the selected coefficients. It can sparsely approximate the original image, and converges faster than the existing local competition based method. Then, we propose a new compression scheme based on the above approximation method. The scheme has compression performance similar to JPEG 2000. The images decoded with the proposed compression scheme appear more pleasant to the human eyes than those with JPEG 2000.展开更多
An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized r...An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.展开更多
A mean-match correlation vector quantizer (MMCVQ) was presented for fast image encoding. In this algorithm, a sorted codebook is generated regarding the mean values of all codewords. During the encoding stage, high co...A mean-match correlation vector quantizer (MMCVQ) was presented for fast image encoding. In this algorithm, a sorted codebook is generated regarding the mean values of all codewords. During the encoding stage, high correlation of the adjacent image blocks is utilized, and a searching range is obtained in the sorted codebook according to the mean value of the current processing vector. In order to gain good performance, proper THd and NS are predefined on the basis of experimental experiences and additional distortion limitation. The expermental results show that the MMCVQ algorithm is much faster than the full-search VQ algorithm, and the encoding quality degradation of the proposed algorithm is only 0.3～0.4 dB compared to the full-search VQ.展开更多
In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! cod...In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer （HVS） evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.展开更多
If the degree distribution is chosen carefully, the irregular low-density parity-check (LDPC) codes can outperform the regular ones. An image transmission system is proposed by combining regular and irregular LDPC cod...If the degree distribution is chosen carefully, the irregular low-density parity-check (LDPC) codes can outperform the regular ones. An image transmission system is proposed by combining regular and irregular LDPC codes with 16QAM/64QAM modulation to improve both efficiency and reliability. Simulaton results show that LDPC codes are good coding schemes over fading channel in image communication with lower system complexity. More over, irregular codes can obtain a code gain of about 0.7 dB compared with regular ones when BER is 10 -4. So the irregular LDPC codes are more suitable for image transmission than the regular codes.展开更多
In this paper, the second generation wavelet transform is applied to image lossless coding, according to its characteristic of reversible integer wavelet transform. The second generation wavelet transform can provide ...In this paper, the second generation wavelet transform is applied to image lossless coding, according to its characteristic of reversible integer wavelet transform. The second generation wavelet transform can provide higher compression ratio than Huffman coding while it reconstructs image without loss compared with the first generation wavelet transform. The experimental results show that the se cond generation wavelet transform can obtain excellent performance in medical image compression coding.展开更多
基金Iran National Science Foundation,Grant/Award Number:99009224。
文摘As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.
基金Electronic Development Fund of Ministry ofInformation Industry of China(No[2004]479)
文摘Based on the ideas of controlling relative quality and rearranging bitplanes, a new ROI coding method for JPEG2000 was proposed, which shifts and rearranges bitplanes in units of bitplane groups. It can code arbitrary shaped ROI without shape coding, and reserve almost arbitrary percent of background information. It also can control the relative quality of progressive decoded images. In addition, it is easy to be implemented and has low computational cost.
基金supported by the National Natural Science Foundationof China (60702012)the Scientific Research Foundation for the Re-turned Overseas Chinese Scholars, State Education Ministry
文摘To compress hyperspectral images, a low complexity discrete cosine transform （DCT）-based distributed source coding （DSC） scheme with Gray code is proposed. Unlike most of the existing DSC schemes, which utilize transform in spatial domain, the proposed algorithm applies transform in spectral domain. Set-partitioning-based approach is applied to reorganize DCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. The extracted refinement bits are Gray encoded. Because of the dependency along the line dimension of hyperspectral images, low density paritycheck-（LDPC）-based Slepian-Wolf coder is adopted to implement the DSC strategy. Experimental results on airborne visible/infrared imaging spectrometer （AVIRIS） dataset show that the proposed paradigm achieves up to 6 dB improvement over DSC-based coders which apply transform in spatial domain, with significantly reduced computational complexity and memory storage.
基金supported in part by the National Natural Science Foundation of China under Grant 61772561,author J.Q,http://www.nsfc.gov.cn/in part by the Key Research and Development Plan of Hunan Province under Grant 2018NK2012,author J.Q,http://kjt.hunan.gov.cn/+7 种基金in part by the Key Research and Development Plan of Hunan Province under Grant 2019SK2022,author Y.T,http://kjt.hunan.gov.cn/in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174,author X.X,http://kxjsc.gov.hnedu.cn/in part by the Science Research Projects of Hunan Provincial Education Department under Grant 19B584,author Y.T,http://kxjsc.gov.hnedu.cn/in part by the Degree&Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154,author J.Q,http://xwb.gov.hnedu.cn/in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant[2019]370-133,author J.Q,http://xwb.gov.hnedu.cn/in part by the Postgraduate Education and Teaching Reform Project of Central South University of Forestry&Technology under Grant 2019JG013,author X.X,http://jwc.csuft.edu.cn/in part by the Natural Science Foundation of Hunan Province(No.2020JJ4140),author Y.T,http://kjt.hunan.gov.cn/in part by the Natural Science Foundation of Hunan Province(No.2020JJ4141),author X.X,http://kjt.hunan.gov.cn/.
文摘In recent years,with the massive growth of image data,how to match the image required by users quickly and efficiently becomes a challenge.Compared with single-view feature,multi-view feature is more accurate to describe image information.The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval.In this paper,a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed.By learning the data correlation between different views,this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval results.This algorithm uses a quantitative hash method to generate binary sequences,and uses the hash code generated by the association features to construct database inverted index files,so as to reduce the memory burden and promote the efficient matching.In order to reduce the matching error of hash code and ensure the retrieval accuracy,this algorithm uses inverted multi-index structure instead of single-index structure.Compared with other advanced image retrieval method,this method has better retrieval performance.
基金This work is funded by Key Scientific Research Projects of Colleges and Universities in Henan Province under Grant 22A460022Training Plan for Young Backbone Teachers in Colleges and Universities in Henan Province under Grant 2021GGJS077.
文摘Traditional three-dimensional(3D)image reconstruction method,which highly dependent on the environment and has poor reconstruction effect,is easy to lead to mismatch and poor real-time performance.The accuracy of feature extraction from multiple images affects the reliability and real-time performance of 3D reconstruction technology.To solve the problem,a multi-view image 3D reconstruction algorithm based on self-encoding convolutional neural network is proposed in this paper.The algorithm first extracts the feature information of multiple two-dimensional(2D)images based on scale and rotation invariance parameters of Scale-invariant feature transform(SIFT)operator.Secondly,self-encoding learning neural network is introduced into the feature refinement process to take full advantage of its feature extraction ability.Then,Fish-Net is used to replace the U-Net structure inside the self-encoding network to improve gradient propagation between U-Net structures,and Generative Adversarial Networks(GAN)loss function is used to replace mean square error(MSE)to better express image features,discarding useless features to obtain effective image features.Finally,an incremental structure from motion(SFM)algorithm is performed to calculate rotation matrix and translation vector of the camera,and the feature points are triangulated to obtain a sparse spatial point cloud,and meshlab software is used to display the results.Simulation experiments show that compared with the traditional method,the image feature extraction method proposed in this paper can significantly improve the rendering effect of 3D point cloud,with an accuracy rate of 92.5%and a reconstruction complete rate of 83.6%.
基金The National Natural Science Foundation of China (No.61362001,61102043,61262084,20132BAB211030,20122BAB211015)the Basic Research Program of Shenzhen(No.JC201104220219A)
文摘A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.
文摘This paper presents an efficient quadtree based fractal image coding scheme in wavelet transform domain based on the wavelet based theory of fractal image compression introduced by Davis. In the scheme, zerotrees of wavelet coefficients are used to reduce the number of domain blocks, which leads to lower bit cost required to represent the location information of fractal coding, and overall entropy constrained optimization is performed for the decision trees as well as for the sets of scalar quantizers and self quantizers of wavelet subtrees. Experiment results show that at the low bit rates, the proposed scheme gives about 1 dB improvement in PSNR over the reported results.
文摘A modular architecture for two dimension (2 D) discrete wavelet transform (DWT) is designed.The image data can be wavelet transformed in real time,and the structure can be easily scaled up to higher levels of DWT.A fast zerotree image coding (FZIC) algorithm is proposed by using a simple sequential scan order and two flag maps.The VLSI structure for FZIC is then presented.By combining 2 D DWT and FZIC,a wavelet image coder is finally designed.The coder is programmed,simulated,synthesized,and successfully verified by ALTERA CPLD.
文摘Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61173183,61672124,61370145,and 11501064)the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund,China(Grant No.MMJJ20170203)+1 种基金the China Postdoctoral Science Foundation(Grant No.2016M590850)the Scientific and Technological Research Program of Chongqing Municipal Education Commission,China(Grant No.KJ1500605)
文摘Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used as the initial value of the chaotic system. Second, the chaotic sequence and Fisher–Yatess scrambling are used to scramble the plaintext,and a sorting scrambling algorithm is used for secondary scrambling. Then, the chaotic sequence and DNA coding rules are used to change the plaintext pixel values, which makes the ciphertext more random and resistant to attacks, and thus ensures that the encrypted ciphertext is more secure. Finally, we add plaintext statistics for pixel-level diffusion to ensure plaintext sensitivity. The experimental results and security analysis show that the new algorithm has a good encryption effect and speed, and can also resist common attacks.
基金Project supported by the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant No.CityU123009)
文摘A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.
基金This work was supported by Scientific Research Starting Project of SWPU[Zheng,D.,No.0202002131604]Major Science and Technology Project of Sichuan Province[Zheng,D.,No.8ZDZX0143]+1 种基金Ministry of Education Collaborative Education Project of China[Zheng,D.,No.952]Fundamental Research Project[Zheng,D.,Nos.549,550].
文摘In the sorting system of the production line,the object movement,fixed angle of view,light intensity and other reasons lead to obscure blurred images.It results in bar code recognition rate being low and real time being poor.Aiming at the above problems,a progressive bar code compressed recognition algorithm is proposed.First,assuming that the source image is not tilted,use the direct recognition method to quickly identify the compressed source image.Failure indicates that the compression ratio is improper or the image is skewed.Then,the source image is enhanced to identify the source image directly.Finally,the inclination of the compressed image is detected by the barcode region recognition method and the source image is corrected to locate the barcode information in the barcode region recognition image.The results of multitype image experiments show that the proposed method is improved by 5+times computational efficiency compared with the former methods,and can recognize fuzzy images better.
文摘Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.
文摘In this paper, we propose a sparse overcomplete image approximation method based on the ideas of overcomplete log-Gabor wavelet, mean shift and energy concentration. The proposed approximation method selects the necessary wavelet coefficients with a mean shift based algorithm, and concentrates energy on the selected coefficients. It can sparsely approximate the original image, and converges faster than the existing local competition based method. Then, we propose a new compression scheme based on the above approximation method. The scheme has compression performance similar to JPEG 2000. The images decoded with the proposed compression scheme appear more pleasant to the human eyes than those with JPEG 2000.
文摘An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.
文摘A mean-match correlation vector quantizer (MMCVQ) was presented for fast image encoding. In this algorithm, a sorted codebook is generated regarding the mean values of all codewords. During the encoding stage, high correlation of the adjacent image blocks is utilized, and a searching range is obtained in the sorted codebook according to the mean value of the current processing vector. In order to gain good performance, proper THd and NS are predefined on the basis of experimental experiences and additional distortion limitation. The expermental results show that the MMCVQ algorithm is much faster than the full-search VQ algorithm, and the encoding quality degradation of the proposed algorithm is only 0.3～0.4 dB compared to the full-search VQ.
基金Project (No. 2004144013) supported by the Chinese Government Scholarship Council, China
文摘In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer （HVS） evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.
文摘If the degree distribution is chosen carefully, the irregular low-density parity-check (LDPC) codes can outperform the regular ones. An image transmission system is proposed by combining regular and irregular LDPC codes with 16QAM/64QAM modulation to improve both efficiency and reliability. Simulaton results show that LDPC codes are good coding schemes over fading channel in image communication with lower system complexity. More over, irregular codes can obtain a code gain of about 0.7 dB compared with regular ones when BER is 10 -4. So the irregular LDPC codes are more suitable for image transmission than the regular codes.
基金Supported by the National Natural Science Foundation of China!( 6 9875 0 0 9)
文摘In this paper, the second generation wavelet transform is applied to image lossless coding, according to its characteristic of reversible integer wavelet transform. The second generation wavelet transform can provide higher compression ratio than Huffman coding while it reconstructs image without loss compared with the first generation wavelet transform. The experimental results show that the se cond generation wavelet transform can obtain excellent performance in medical image compression coding.
