scholarly journals Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection

2021 ◽  
Vol 18 (5) ◽  
pp. 6771-6789
Author(s):  
Hongyan Xu ◽  
Keyword(s):  
Edge Detection ◽  
Digital Media ◽  
Copyright Protection ◽  
Detection Rate ◽  
Signal To Noise Ratio ◽  
Edge Computing ◽  
Absolute Difference ◽  
Watermark Image ◽  
Signal To Noise ◽  
Noise Ratio

<abstract> <p>With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.</p> </abstract>

scholarly journals Analysis and Implementation of Enhanced Image Inpainting method using adjustable patch sizes

2021 ◽  
Vol 9 (3) ◽  
pp. 310-317
Keyword(s):  
Mean Square Error ◽  
Patch Size ◽  
Signal To Noise Ratio ◽  
Image Inpainting ◽  
Absolute Difference ◽  
Mean Square ◽  
Patch Selection ◽  
Signal To Noise ◽  
Distance Method ◽  
Noise Ratio

Image inpainting is the process of reconstruction of the damaged image and removal of unwanted objects in an image. In the image inpainting process patch priority andselection of best patch playsa major role. The patch size is also considered for producing good results in the image inpainting. In this paper patch priority is obtained by introducing a regularization factor (ɷ). The best patch selection is acquired by using the Sum of Absolute Difference (SAD) distance method. The results of inpainting are investigated with adjustable patch sizes of 5×5, 7×7, 9×9, 11×11, and 13×13 for the proposed method. The performance of these adjustable patch sizes is observed by using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The best suitable patch size for good inpainting is announced based on the values of PSNR and MSE.

scholarly journals COALESCENCE RATE OF SUPERMASSIVE BLACK HOLE BINARIES DERIVED FROM COSMOLOGICAL SIMULATIONS: DETECTION RATES FOR LISA AND ET

2011 ◽  
Vol 20 (12) ◽  
pp. 2399-2417 ◽  
Author(s):  
CH. FILLOUX ◽  
J. A. DE FREITAS PACHECO ◽  
F. DURIER ◽  
J. C. N. DE ARAUJO
Keyword(s):  
Black Holes ◽  
Gravitational Wave ◽  
Detection Rate ◽  
Signal To Noise Ratio ◽  
Supermassive Black Holes ◽  
Frequency Interval ◽  
Signal To Noise ◽  
Cosmological Simulations ◽  
Coalescence Rate ◽  
Noise Ratio

The coalescence history of massive black holes has been derived from cosmological simulations, in which the evolution of those objects and that of the host galaxies are followed in a consistent way. The present study indicates that supermassive black holes having masses greater than ~ 109 M⊙ underwent up to 500 merger events along their history. The derived coalescence rate per comoving volume and per mass interval permitted to obtain an estimate of the expected detection rate distribution of gravitational wave signals ("ring-down") along frequencies accessible by the planned interferometers either in space (LISA) or in the ground (Einstein). For LISA, in its original configuration, a total detection rate of about 15 yr-1 is predicted for events having a signal-to-noise ratio equal to 10, expected to occur mainly in the frequency range 4–9 mHz. For the Einstein gravitational wave telescope, one event each 14 months down to one event each four years is expected with a signal-to-noise ratio of 5, occurring mainly in the frequency interval 10–20 Hz. The detection of these gravitational signals and their distribution in frequency would be in the future an important tool able to discriminate among different scenarios explaining the origin of supermassive black holes.

scholarly journals DEVELOPMENT OF A SYSTEM FOR DIGITAL WATERMARKS EMBEDDING INTO IMAGES BASED ON DCT-LWT-SVD

2020 ◽  
pp. 23-31
Author(s):  
A.V. Akhmametieva ◽  
A.A. Baraniuk
Keyword(s):  
Wavelet Transform ◽  
Copyright Protection ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Low Frequency ◽  
Digital Watermark ◽  
Signal To Noise ◽  
Actual Problem ◽  
Noise Ratio ◽  
Salt And Pepper

Copyright protection of digital content is a rather actual problem of humanity in the 21st century. Misuses of multimedia content is very common, and their number is growing with each passing day. One type of copyright protection is the embedding of digital watermark (DW) in the content. In this paper a new method of embedding digital watermark into image using discrete cosine transform, lifting wavelet transform (LWT) with maternal wavelet "Dobeshi-8" and singular coefficients decomposition is proposed. Embedding is performed into the first singular number of the low frequency wavelet transform region. As a digital watermark, we will use a grayscale image normalized to a range from zero to ten to provide a high peak signal-to-noise ratio (PSNR). The research analyzed the developed method: the method of embedding and detecting information was tested for its resistance to various types of attacks, namely: application of noise overlay (Gauss and pulse noise, "salt and pepper"), "unsharp" filter and median filter, and compression attack (with quality coefficients for a complete container from 60 to 100). As a result of the conducted testing, it was established that the method is quite resistant to all the attacks, except for the "unsharp" filtering (the resulting performance is not satisfactory). The method showed good results in peak signal-to-noise ratio - the average PSNR value is 50.5 dB, as well as high rates of similarity between the embedded DW and the extracted one - from 77% to 97.6% while saving the full container in a lossless format, and up to 53, 05 dB and 91.96% while saving the image in a lossless format (JPEG).

scholarly journals Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar

2020 ◽  
Author(s):  
Pyry Pentikäinen ◽  
Ewan James O'Connor ◽  
Antti Juhani Manninen ◽  
Pablo Ortiz-Amezcua
Keyword(s):  
Signal To Noise Ratio ◽  
Focal Length ◽  
Quantitative Information ◽  
Absolute Difference ◽  
Beam Diameter ◽  
Doppler Lidar ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio ◽  
Two Parameters

Abstract. Doppler lidars provide two measured parameters, radial velocity and signal-to-noise ratio, from which winds and turbulent properties are routinely derived. Attenuated backscatter, which gives quantitative information on aerosols, clouds, and precipitation in the atmosphere, can be used in conjunction with the winds and turbulent properties to create a sophisticated classification of the state of the atmospheric boundary layer. Calculating attenuated backscatter from the signal-to-noise ratio requires accurate knowledge of the telescope focus function, which is usually unavailable. Inaccurate assumptions of the telescope focus function can significantly deform attenuated backscatter profiles, even if the instrument is focused at infinity. Here, we present a methodology for deriving the telescope focus function using a co-located ceilometer for Halo Photonics Streamline and XR pulsed heterodyne Doppler lidars. The method derives two parameters of the telescope focus function, the effective beam diameter and the effective focal length of the telescope. Additionally, the method provides uncertainty estimates for the retrieved attenuated backscatter profile arising from uncertainties in deriving the telescope function, together with standard measurement uncertainties from the signal-to-noise ratio. The method is best suited for locations where the absolute difference in aerosol extinction at the ceilometer and Doppler lidar wavelengths is small.

scholarly journals Modifikasi Ant Colony Optimization Berdasarkan Gradient Untuk Deteksi Tepi Citra

2015 ◽  
Vol 6 (3) ◽  
Author(s):  
Febri Liantoni ◽  
Nanik Suciati ◽  
Chastine Fatichah
Keyword(s):  
Edge Detection ◽  
Ant Colony Optimization ◽  
Signal To Noise Ratio ◽  
Ant Colony ◽  
Test Results ◽  
Signal To Noise ◽  
Average Value ◽  
Image Edge ◽  
Noise Ratio ◽  
Better Than

Abstract. Ant Colony Optimization (ACO) is an optimization algorithm which can be used for image edge detection. In traditional ACO, the initial ant are randomly distributed. This condition can cause an imbalance ants distribution. Based on this problem, a modified ant distribution in ACO is proposed to optimize the deployment of ant based gradient. Gradient value is used to determine the placement of the ants. Ants are not distributed randomly, but are placed in the highest gradient. This method is expected to be used to optimize the path discovery. Based on the test results, the use of the proposed ACO modification can obtain an average value of the Peak Signal to Noise Ratio (PSNR) of 12.724. Meanwhile, the use of the traditional ACO can obtain an average value of PSNR of 12.268. These results indicate that the ACO modification is capable of generating output image better than traditional ACO in which ants are initially distributed randomly.Keywords: Ant Colony Optimization, gradient, Edge Detection, Peak Signal to Noise Ratio Abstrak. Ant Colony Optimization (ACO) merupakan algoritma optimasi, yang dapat digunakan untuk deteksi tepi pada citra Pada ACO tradisional, semut awal disebarkan secara acak. Kondisi ini dapat menyebabkan ketidakseimbangan distribusi semut. Berdasarkan permasalahan tersebut, modifikasi distribusi semut pada ACO diusulkan untuk mengoptimalkan penempatan semut berdasarkan gradient. Nilai gradient digunakan untuk menentukan penempatan semut. Semut tidak disebar secara acak akan tetapi ditempatkan di gradient tertinggi. Cara ini diharapkan dapat digunakan untuk optimasi penemuan jalur. Berdasarkan hasil uji coba, dengan menggunakan ACO modifikasi yang diusulkan dapat diperoleh nilai rata-rata Peak Signal to Noise Ratio (PSNR) 12,724. Sedangkan, menggunakan ACO tradisional diperoleh nilai rata-rata PSNR 12,268. Hasil ini menunjukkan bahwa ACO modifikasi mampu menghasilkan citra keluaran yang lebih baik dibandingkan ACO tradisional yang sebaran semut awalnya dilakukan secara acak.Kata Kunci: Ant Colony Optimization, gradient, deteksi tepi, Peak Signal to Noise Ratio

scholarly journals Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar

2020 ◽  
Vol 13 (5) ◽  
pp. 2849-2863
Author(s):  
Pyry Pentikäinen ◽  
Ewan James O'Connor ◽  
Antti Juhani Manninen ◽  
Pablo Ortiz-Amezcua
Keyword(s):  
Signal To Noise Ratio ◽  
Focal Length ◽  
Quantitative Information ◽  
Absolute Difference ◽  
Beam Diameter ◽  
Doppler Lidar ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio ◽  
Two Parameters

Abstract. Doppler lidars provide two measured parameters, radial velocity and signal-to-noise ratio, from which winds and turbulent properties are routinely derived. Attenuated backscatter, which gives quantitative information on aerosols, clouds, and precipitation in the atmosphere, can be used in conjunction with the winds and turbulent properties to create a sophisticated classification of the state of the atmospheric boundary layer. Calculating attenuated backscatter from the signal-to-noise ratio requires accurate knowledge of the telescope focus function, which is usually unavailable. Inaccurate assumptions of the telescope focus function can significantly deform attenuated backscatter profiles, even if the instrument is focused at infinity. Here, we present a methodology for deriving the telescope focus function using a co-located ceilometer for pulsed heterodyne Doppler lidars. The method was tested with Halo Photonics StreamLine and StreamLine XR Doppler lidars but should also be applicable to other pulsed heterodyne Doppler lidar systems. The method derives two parameters of the telescope focus function, the effective beam diameter and the effective focal length of the telescope. Additionally, the method provides uncertainty estimates for the retrieved attenuated backscatter profile arising from uncertainties in deriving the telescope function, together with standard measurement uncertainties from the signal-to-noise ratio. The method is best suited for locations where the absolute difference in aerosol extinction at the ceilometer and Doppler lidar wavelengths is small.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

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