Expanding the property profile of Bayfol HX® film towards NIR recording and ultra high index modulation

2021 ◽  
Author(s):  
Friedrich-Karl Bruder ◽  
Johannes Frank ◽  
Sven Hansen ◽  
Alexander Lorenz ◽  
Christel Manecke ◽  
...  
Keyword(s):  
High Index ◽  
Property Profile ◽  
Index Modulation

Expanded property profile of Bayfol HX® film towards NIR recording and ultra-high index modulation

2021 ◽  
Author(s):  
Friedrich-Karl Bruder ◽  
Johannes Frank ◽  
Sven Hansen ◽  
Alexander Lorenz ◽  
Christel Manecke ◽  
...  
Keyword(s):  
High Index ◽  
Property Profile ◽  
Index Modulation

Expanding the property profile of Bayfol HX(R) film towards NIR recording and ultra-high index modulation

2021 ◽  
Author(s):  
Friedrich-Karl Bruder ◽  
Johannes Frank ◽  
Sven Hansen ◽  
Alexander Lorenz ◽  
Christel Manecke ◽  
...  
Keyword(s):  
High Index ◽  
Property Profile ◽  
Index Modulation

Signal breathing losses in filters based on optical channel with high index modulation

2017 ◽  
Vol 73 ◽  
pp. 9-15 ◽  
Author(s):  
Kamal Ghoumid ◽  
El Miloud Ar-reyouchi ◽  
Amina Ghadban ◽  
Bekkay Hajji ◽  
Reda Yahiaoui ◽  
...  
Keyword(s):  
High Index ◽  
Optical Channel ◽  
Index Modulation

The usefulness of high index low symmetry zone axes for holz line analysis

1987 ◽  
Vol 45 ◽  
pp. 384-385
Author(s):  
C. M. Sung ◽  
D. B. Williams
Keyword(s):  
Lattice Parameter ◽  
High Order ◽  
Zone Axis ◽  
High Index ◽  
High Symmetry ◽  
Second Phases ◽  
Line Patterns ◽  
Low Symmetry ◽  
Line Analysis

Researchers have tended to use high symmetry zone axes (e.g. <111> <114>) for High Order Laue Zone (HOLZ) line analysis since Jones et al reported the origin of HOLZ lines and described some of their applications. But it is not always easy to find HOLZ lines from a specific high symmetry zone axis during microscope operation, especially from second phases on a scale of tens of nanometers. Therefore it would be very convenient if we can use HOLZ lines from low symmetry zone axes and simulate these patterns in order to measure lattice parameter changes through HOLZ line shifts. HOLZ patterns of high index low symmetry zone axes are shown in Fig. 1, which were obtained from pure Al at -186°C using a double tilt cooling holder. Their corresponding simulated HOLZ line patterns are shown along with ten other low symmetry orientations in Fig. 2. The simulations were based upon kinematical diffraction conditions.

Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM

2018 ◽  
Vol 6 (3) ◽  
pp. 405
Author(s):  
IRMA SAFITRI ◽  
NUR IBRAHIM ◽  
HERLAMBANG YOGASWARA
Keyword(s):  
Wavelet Transform ◽  
Compressive Sensing ◽  
Audio Watermarking ◽  
Quantization Index Modulation ◽  
Computationally Efficient ◽  
Black And White ◽  
Additional Information ◽  
Audio Files ◽  
Index Modulation ◽  
Mp3 Compression

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.

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