the core of intelligent manufacturing is Cyber-Physical system. In order to establish high frequency sampling of Cyber-Physical system, massive data is needed. It is necessary to study the efficient transmission techn...
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ISBN:
(数字)9781728146898
ISBN:
(纸本)9781728146904
the core of intelligent manufacturing is Cyber-Physical system. In order to establish high frequency sampling of Cyber-Physical system, massive data is needed. It is necessary to study the efficient transmission technology of real-time data. data compression is through the omitted part is not necessary or redundant, transfer and storage in finite strip width, and storage space for more information of a technical means. Embedded Wavelet coding (Embedded Zero tree Wavelet, EZW) is based on Wavelet transform multi-resolution analysis technology, extract the Embedded Zero tree, and variable length of quantization and coding compression, transmission and decompression algorithm. this paper mainly studies the numerical control machine tool electric control instruction domain representative of the current loop of data in the data for one dimensional data was designed based on the EZW algorithm binary tree structure of zero tree and Huffman encoding to achieve further compression. Verification experiment and application results showed that, the algorithm on the basis of the guarantee accuracy has good compression ratio and efficiency.
this paper researches the key re-encryption technology of the key management server, and solves the storage security problem faced by massive key management under content association key encryption mechanism. the key ...
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Bayer Colour Filter Array is a matrix of photosensors covered with red, green, and blue colour filters. this setup is advantageous in smartphones as only a third of the required data is captured by the sensor in the c...
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ISBN:
(数字)9781728106304
ISBN:
(纸本)9781728106311
Bayer Colour Filter Array is a matrix of photosensors covered with red, green, and blue colour filters. this setup is advantageous in smartphones as only a third of the required data is captured by the sensor in the camera. the rest of the components based on the colour format can be interpolated using a suitable algorithm to arrive at a full-colour image. Increasing the resolution of the camera sensor will translate to increased bandwidth in the image signal processing pipeline, and consequently power consumption. In addition to that, the bit depth is also on the rise to enhance the colours. these two factors will create a huge impact on the data to be handled in the pertinent processor. Hence, compression of the Bayer data is of immense significance. the existing standard compression schemes can be adapted to suit the Bayer format. Also, several compression schemes, specific to Bayer format have been proposed. Two compression methods, viz. JPEG-LS and Hierarchical Prediction based compression have been tested and the corresponding results are presented in this paper. the former is a standard while the latter has been proposed keeping the Bayer format in mind. Modelling of the algorithms shows that JPEG-LS is best suited in the use cases where lossless compression is desirable, and Hierarchical Prediction based compression is the better option where some amount of loss is acceptable.
Watermarking is a method to protect the copyright of a work. Watermark can be either text, image, audio, or video. data insertion is done in such a way so that the data will not damage the secured digital information....
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ISBN:
(数字)9781728151182
ISBN:
(纸本)9781728151199
Watermarking is a method to protect the copyright of a work. Watermark can be either text, image, audio, or video. data insertion is done in such a way so that the data will not damage the secured digital information. the datathat is inserted cannot be removed from the digital information and must be able to be re-extracted. this research will analyze the compressive sampling based on DCT-DWT for watermark compression on video watermarking using DWT-SVD and OMP reconstruction with RS Code to check on the error bit. Our system produces BER 0.25, PSNR 54.577 dB of PSNR, and MSE 0.215. this system is resistant to rescaling attack.
In order to provide secure retrieval for encrypted digital images in cloud-based system, a secure searchable imageencryption algorithm based on Block Truncation coding (BTC) and Henon chaotic map is presented. Henon ...
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ISBN:
(纸本)9783030000127;9783030000110
In order to provide secure retrieval for encrypted digital images in cloud-based system, a secure searchable imageencryption algorithm based on Block Truncation coding (BTC) and Henon chaotic map is presented. Henon Chaotic map is used to encrypt two quantization levels of BTC compressed images, and a pseudo random sequence is created by chaotic map to scramble the bit plane of each sub-block. the feature value of each sub-block is computed according to the relationship between the number of 1s and 0s in the corresponding bit plane. the encrypted image retrieval can be achieved by comparing the normalized correlation coefficients between the feature vectors. Experimental results show that the proposed scheme has satisfactory retrieval accuracy and security. Meanwhile, it has low computational cost and can be used for encrypted images retrieval in the cloud.
images are the main media type on the Internet. image compression efficiency plays a key role in image transmission and storage. Recently, Google opened the source code of Guetzli, a subjective quality guided algorith...
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ISBN:
(纸本)9781538653746
images are the main media type on the Internet. image compression efficiency plays a key role in image transmission and storage. Recently, Google opened the source code of Guetzli, a subjective quality guided algorithm which can increase the compression rate by 30% compared withthe most popular image compression format of JPEG. However, the running speed of Guetzli is too slow. To solve the problem, we propose a modified method based on Guetzli by making the search window variable instead of a constant value, which is able to obtain a higher processing speed while lose an acceptable compression rate. Finally, we present a model with about 70% time cost and nearly the same data size compared withthe original Guetzli.
Now-a-days due to the huge increase in the size of imagedata Lossy image compression is highly used to reduce the image size but without having huge data *** compression using SVD coding algorithm, Compressive Encode...
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ISBN:
(纸本)9781538611203;9781538611197
Now-a-days due to the huge increase in the size of imagedata Lossy image compression is highly used to reduce the image size but without having huge data *** compression using SVD coding algorithm, Compressive Encoders and using prediction Error and Vectorization ratio are proved to have numerous application in image *** compression using SVD coding algorithm involves refactoring of a digital image into three matrixes. Refactoring is achieved by using singular values, and the image is represented with a smaller set of values. though,encoders cannot directly optimize due to the inherentNon-differentiability of the compression loss but it isoutperforming recently proposed approaches based on *** PE-VQ method is based on Prediction Error and Vector Quantisation techniques where image performance is determined using compression ratio and PSNR values using databases namely CLEF med 2009, Corel 1k and standard images like Lena, Barbara ***,in this research article a comparative study of these three techniquesis carried out where their image quality and compression ratio is examined by using the PSNR values and compression ratios.
In this paper, medical image compression technique is presented based on adaptive Scan Wavelet Difference Reduction (ASWDR). It helps to save the storage space and transmission bandwidth of tele-healthcare system. the...
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ISBN:
(纸本)9781509027972
In this paper, medical image compression technique is presented based on adaptive Scan Wavelet Difference Reduction (ASWDR). It helps to save the storage space and transmission bandwidth of tele-healthcare system. the presented compression scheme has evaluated for different ultrasound image of different cases. the ASWDR technique is exploited with different wavelet filters and obtained the different efficiency of compression as per distinctive sparse characteristics. However, the performance of presented compression scheme is evaluated with fidelity assessments as well as human vision perception for compression and reconstruction. As seen the results, compression of the image is obtained up to 45:1 with 99% of structural similarity of the original and compressed image.
Transform coding plays an important role in image and video compression. the Karhunen-Loéve transform (KLT) is the optimal transform for its full decorrelation ability. However, there is no general algorithm that...
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ISBN:
(纸本)9781538653746
Transform coding plays an important role in image and video compression. the Karhunen-Loéve transform (KLT) is the optimal transform for its full decorrelation ability. However, there is no general algorithm that enables its fast computation since the KLT is data dependent. Instead, the discrete cosine transform (DCT) is used widely for its good energy compaction and fast implementation algorithm. the DCT matrix can be derived by letting the correlation coefficient ρ be 1 for the Markov-1 model of signal. Since such a perfectly correlated signal is rare the DCT is usually suboptimal. In this letter, taking the real image signal into consideration and setting the ρ to be a value ρ* closer to the actual correlation coefficient in the real image, we obtain the data independent KLT (diKLT). Experimental results show that the diKLT outperforms DCT in terms of the mean square error (MSE) and structural similarity (SSIM) as long as the ρ* is big enough and the retained transform coefficients are sufficient. Although the superiority of diKLT over DCT is not prominent the advantage that a transform independent of data outperforms DCT is worthy to be noticed.
Compress sensing has advantage of simultaneous sensing and data compression. In recent years block compressive sensing (BCS) is celebrated because of its low encoding complexity. In this paper FOCUSS reconstruction al...
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ISBN:
(纸本)9781538683408
Compress sensing has advantage of simultaneous sensing and data compression. In recent years block compressive sensing (BCS) is celebrated because of its low encoding complexity. In this paper FOCUSS reconstruction algorithm based on BCS frame work is proposed utilizing iterative re-weighted l 1 norm minimization. In proposed approach the required sparsity was attained using l 1 norm minimization and 2D-Median filter is implemented as smoothing operator for removing blocking artifacts. the performance of reconstruction algorithm is verified on different data sets and results obtained from analysis reveal that the suggested approach for image reconstruction offers significant compression performance in contrast to existing techniques.
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