scholarly journals Performance analysis of two stage adaptive FIR Filter Algorithms for PLI and BW artifact cancellation in ECG

2018 ◽  
Vol 7 (1.8) ◽  
pp. 123
Author(s):  
B. Bhaskara Rao ◽  
B. Prabhakara Rao
Keyword(s):  
Mean Square Error ◽  
Adaptive Filters ◽  
Signal To Noise Ratio ◽  
Adaptive Algorithms ◽  
Mean Square ◽  
Signal To Noise ◽  
Two Stage ◽  
Baseline Wander ◽  
Power Line Interference ◽  
Line Interference

Electrocardiogram (ECG) is a measure of the electrical movement of the heart, and is obtained by surface electrodes at standardized locations on the patient’s chest. During acquisition, various artifacts/noises such as power-line interference (PLI), baseline wander (BW), muscle artifacts (MA) and motion artifacts (EM) obscure the ECG. It is important that these artifacts are minimized for the clinicians to make better diagnosis on heart problems. This paper researches the creative idea of adaptive noise cancellation (ANC) using two stage form of adaptive filters. The concept of cascading and its algorithm for real-time application is simulated on MATLAB. The proposed algorithm utilizes two adaptive filters to estimate gradients accurately which results in good adaptation and performance. The objective of the present investigation is to provide solution in order to improve the performance of noise canceller in terms of filter parameters which are obtained with the help of adaptive algorithms. Different kinds of two stage ANC algorithms are used to eliminate artifacts in ECG by considering the noises such as power line interference and baseline wander. The simulation results show that the performance of the two stage ANC is superior to the conventional single stage ANC system in terms of higher signal-to-noise ratio. Two stage adaptive algorithms are applied on real time ECG signals and compared their performance with the conventional single stage adaptive algorithms in terms of parameters Signal-to-Noise Ratio (SNR), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Distortion.

scholarly journals Audio steganography based on least significant bits algorithm with 4D grid multi-wing hyper-chaotic system

2022 ◽  
Vol 12 (1) ◽  
pp. 320
Author(s):  
Hussein Abdulameer Abdulkadhim ◽  
Jinan Nsaif Shehab
Keyword(s):  
Mean Square Error ◽  
Chaotic System ◽  
Signal To Noise Ratio ◽  
Secret Message ◽  
Security Level ◽  
Mean Square ◽  
Signal To Noise ◽  
Protection Level ◽  
Voice Message ◽  
Least Significant Bits

Although variety in hiding methods used to protect data and information transmitted via channels but still need more robustness and difficulty to improve protection level of the secret messages from hacking or attacking. Moreover, hiding several medias in one media to reduce the transmission time and band of channel is the important task and define as a gain channel. This calls to find other ways to be more complexity in detecting the secret message. Therefore, this paper proposes cryptography/steganography method to hide an audio/voice message (secret message) in two different cover medias: audio and video. This method is use least significant bits (LSB) algorithm combined with 4D grid multi-wing hyper-chaotic (GMWH) system. Shuffling of an audio using key generated by GMWH system and then hiding message using LSB algorithm will provide more difficulty of extracting the original audio by hackers or attackers. According to analyses of obtained results in the receiver using peak signal-to-noise ratio (PSNR)/mean square error (MSE) and sensitivity of encryption key, the proposed method has more security level and robustness. Finally, this work will provide extra security to the mixture base of crypto-steganographic methods.

scholarly journals An Image Steganography Algorithm using Fractional Discrete Wavelet Transform with Advanced Encryption System

2020 ◽  
Vol 9 (5) ◽  
pp. 541-546
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

The research constitutes a distinctive technique of steganography of image. The procedure used for the study is Fractional Random Wavelet Transform (FRWT). The contrast between wavelet transform and the aforementioned FRWT is that it comprises of all the benefits and features of the wavelet transform but with additional highlights like randomness and partial fractional value put up into it. As a consequence of the fractional value and the randomness, the algorithm will give power and a rise in the surveillance layers for steganography. The stegano image will be acquired after administrating the algorithm which contains not only the coated image but also the concealed image. Despite the overlapping of two images, any diminution in the grade of the image is not perceived. Through this steganographic process, we endeavor for expansion in surveillance and magnitude as well. After running the algorithm, various variables like Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR) are deliberated. Through the intended algorithm, a rise in the power and imperceptibility is perceived and it can also support diverse modification such as scaling, translation and rotation with algorithms which previously prevailed. The irrefutable outcome demonstrated that the algorithm which is being suggested is indeed efficacious.

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.

Joint demosaicing of colour and polarisation from filter arrays

2021 ◽  
Vol 2021 (29) ◽  
pp. 288-293
Author(s):  
Alexandra Spote ◽  
Pierre-Jean Lapray ◽  
Jean-Baptiste Thomas ◽  
Ivar Farup
Keyword(s):  
Mean Square Error ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Mean Square ◽  
Interpolation Algorithm ◽  
Signal To Noise ◽  
Image Content ◽  
Filter Array ◽  
Array Imaging

This article considers the joint demosaicing of colour and polarisation image content captured with a Colour and Polarisation Filter Array imaging system. The Linear Minimum Mean Square Error algorithm is applied to this case, and its performance is compared to the state-of-theart Edge-Aware Residual Interpolation algorithm. Results show that the LMMSE demosaicing method gives statistically higher scores on the largest tested database, in term of peak signal-to-noise ratio relatively to a CPFA-dedicated algorithm.

scholarly journals PERBANDINGAN METODE UNTUK PERBAIKAN KUALITAS CITRA MAMMOGRAM

2016 ◽  
Vol 7 (2) ◽  
pp. 657
Author(s):  
Hanifah Rahmi Fajrin
Keyword(s):  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Region Of Interest ◽  
Contourlet Transform ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

Kanker payudara merupakan pembunuh nomor satu pada wanita di seluruh dunia. Sejauh ini, deteksi dari kanker payudara hanya menggunakan mata telanjang dan berdasarkan jam terbang (pengalaman) dari dokter dan radiologis. Terdapat beberapa kelemahan dalam menganalisis mammogram payudara guna mendeteksi keberadaan kanker payudara. Hal ini bisa diakibatkan oleh sel kanker yang tertutup oleh noise, kontras citra yang rendah dan faktor manusiawi lainnya seperti : kelelahan, mood, dan lainnya. Untuk meminimalisir hal tersebut dibutuhkan suatu metode yang dapat membantu dokter dalam menganalisis citra mammogram payudara. Pada penelitian ini, dilakukan suatu proses yang bertujuan untuk meningkatkan kualitas mammogram agar lebih memudahkan dokter dalam mendiagnosis kelainan pada payudara. Citra yang diolah merupakan citra mammogram yang tidak dipangkas dan tidak disegmentasi pada bagian Region of Interest (ROI), melainkan keseluruhan citra payudara setelah dihilangkan background yang berlebihan. Tahapan pada proses peningkatan kuliatas citra mammogram ini (pra pengolahan) terdiri dari : menghilangkan label atau artifak yang ditemukan pada mammogram, meng-crop citra pada bagian payudara saja (menghilangkan background), memperbaiki kontras citra dengan membandingkan beberapa metode yaitu: CLAHE, Non Subsampled Contourlet Transform (NSCT), Contras Stretching (CS) dan selanjutnya dilakukan smoothing dengan menggunakan filter median. Kinerja dari setiap metode dihitung dengan mencari nilai Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR) citra. Dari nilai MSE dan PSNR yang didapatkan, ditemukan nilai MSE dan PSNR terbaik pada metode NSCT dengan nilai 50.20878 db 31.75332 db. Kata kunci: CLAHE, NSCT, CS, median filter.

scholarly journals A powerful notch filter for PLI cancelation

2021 ◽  
Author(s):  
Ali Mobaien ◽  
Arman Kheirati Roonizi ◽  
Reza Boostani
Keyword(s):  
Signal To Noise Ratio ◽  
Effective Means ◽  
Synthetic Data ◽  
Notch Filter ◽  
Least Square ◽  
Noise Levels ◽  
Signal To Noise ◽  
Power Line Interference ◽  
Zero Phase ◽  
Line Interference

<div>Abstract—In this work, we present a powerful notch filter for power-line interference (PLI) cancelation from biomedical signals. This filter has a unit gain and a zero-phase response. Moreover, the filter can be implemented adaptively to adjust its bandwidth based on the signal-to-noise ratio. To realize this filter, a dynamic model is defined for PLI based on its sinusoid property. Then, a constrained least square error estimation is used to emerge the PLI based on the observations while the constraint is the PLI dynamic. At last, the estimated PLI is subtracted from recordings. The proposed filter is assessed using synthetic data and real biomedical recordings in different noise levels. The results demonstrate this filter as a very powerful and effective means for canceling the PLI out.</div>

scholarly journals A powerful notch filter for PLI cancelation

2021 ◽  
Author(s):  
Ali Mobaien ◽  
Arman Kheirati Roonizi ◽  
Reza Boostani
Keyword(s):  
Signal To Noise Ratio ◽  
Effective Means ◽  
Synthetic Data ◽  
Notch Filter ◽  
Least Square ◽  
Noise Levels ◽  
Signal To Noise ◽  
Power Line Interference ◽  
Zero Phase ◽  
Line Interference

<div>Abstract—In this work, we present a powerful notch filter for power-line interference (PLI) cancelation from biomedical signals. This filter has a unit gain and a zero-phase response. Moreover, the filter can be implemented adaptively to adjust its bandwidth based on the signal-to-noise ratio. To realize this filter, a dynamic model is defined for PLI based on its sinusoid property. Then, a constrained least square error estimation is used to emerge the PLI based on the observations while the constraint is the PLI dynamic. At last, the estimated PLI is subtracted from recordings. The proposed filter is assessed using synthetic data and real biomedical recordings in different noise levels. The results demonstrate this filter as a very powerful and effective means for canceling the PLI out.</div>

scholarly journals Implementasi Steganografi Video dengan Menggunakan Metode Egypt, Least Significant Bit (LSB) dan Least Significant Bit (LSB) Fibonacci Edge Pixel

2020 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Ranida Pradita ◽  
Ida Nurhaida
Keyword(s):  
Mean Square Error ◽  
Digital Image ◽  
Digital Video ◽  
3D Model ◽  
Signal To Noise Ratio ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Edge Pixel ◽  
Audio Video

Seiring dengan perkembangan teknologi 5G, penyebaran dengan menggunakan video semakin besar dan mudah. Penyebaran informasi baik yang tersembunyi atau tidak semakin mudah disebarluaskan dengan menggunakan internet. Steganografi adalah cara menyembunyikan informasi dalam image atau video. Steganografi berbentuk digital image, text, audio, video, 3D model, dan lain-lain. Media digital yang popularitasnya paling tinggi dalam penelitian algoritma steganografi dengan menggunakan media digital image. Tulisan ini menggunakan media digital video karna media penelitian sebelumnya menggunakan media digital image. Pada tulisan ini akan diulas dan dianalis tentang video steganografi dengan menggunakan metode Egypt, Least Significant Bit (LSB), dan Least Significant Bit (LSB) Fibonacci Edge Pixel. Analisis video steganografi ini bertujuan untuk mendeteksi video yang mengandung unsur pesan rahasia yang kemungkinan untuk pengintaian. Hasil Peak Signal-to-Noise Ratio (PSNR) yang didapat dari penelitian ini rata-rata 40.46 dB dan menghasilkan rata-rata presentase similarity 30.67 %. Rata-rata Mean Square Error (MSE) pada penelitian ini adalah sebesar 0.50657. Untuk metode yang paling optimal yang digunakan dalam video steganografi adalah dengan menggunakan Metode Egypt.

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