scholarly journals Performance Analysis of Various Filters for De-Speckling of Thyroid Ultrasound Images

2019 ◽  
Vol 9 (2) ◽  
pp. 910-917
Keyword(s):  
Mean Square Error ◽  
Image Quality Assessment ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

Thyroid ultrasonography is the most common and extremely useful, safe, and cost effective way to image the thyroid gland and its pathology. However, an inherent characteristic of Ultrasound (US) imaging is the presence of multiplicative speckle noise. Speckle noise reduces the ability of an observer to distinguish fine details, make diagnosis more difficult. It limits the effective implementation of image analysis steps such as edge detection, segmentation and classification. The main objective of this study is to compare the performance of various spatial and frequency domain filters so as to identify efficient and optimum filter for de-speckling Thyroid US images. The performance of these filters is evaluated using the image quality assessment parameters Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE) and Root Mean Square Error (RMSE) for different speckle variance. Experimental work revealed that kuan filter resulted in higher PSNR, SNR, SSIM and least MSE, RMSE values compared to other filters

Despeckling of Carotid Artery Ultrasound Images with a Calculus Approach

2019 ◽  
Vol 15 (4) ◽  
pp. 414-426 ◽  
Author(s):  
S. Latha ◽  
Dhanalakshmi Samiappan
Keyword(s):  
Carotid Artery ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Structural Similarity ◽  
Speckle Noise ◽  
Absolute Error ◽  
Block Matching ◽  
Ultrasound Images ◽  
Mean Square ◽  
Integral Calculus

<P>Background: Carotid artery images indicate any presence of plaque content, which may lead to atherosclerosis and stroke. Early identification of the disease is possible by taking B-mode ultrasound images in the carotid artery. Speckle is the inherent noise content in the ultrasound images, which essentially needs to be minimized. </P><P> Objective: The objective of the proposed method is to convert the multiplicative speckle noise into additive, after which the frequency transformations can be applied. </P><P> Method: The method uses simple differentiation and integral calculus and is named variable gradient summation. It differs from the conventional homomorphic filter, by preserving the edge features to a great extent and better denoising. The additive image is subjected to wavelet decomposition and further speckle filtering with three different filters Non Local Means (NLM), Vectorial Total Variation (VTV) and Block Matching and 3D filtering (BM3D) algorithms. By this approach, the components dependent on the image are identified and the unwanted noise content existing in the high frequency portion of the image is removed. </P><P> Results & Conclusion: Experiments conducted on a set of 300 B-mode ultrasound carotid artery images and the simulation results prove that the proposed method of denoising gives enhanced results as compared to the conventional process in terms of the performance evaluation methods like peak signal to noise ratio, mean square error, mean absolute error, root mean square error, structural similarity, quality factor, correlation and image enhancement factor.</P>

ANALISIS SENSITIVITAS VIDEO MPEG-4 BERDASARKAN STRUKTUR FRAME PADA TRANSMISI DVB-T

2020 ◽  
Vol 25 (2) ◽  
pp. 86-97
Author(s):  
Sandy Suryo Prayogo ◽  
Tubagus Maulana Kusuma
Keyword(s):  
Deep Learning ◽  
Bit Error Rate ◽  
Error Rate ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Signal To Noise ◽  
Structural Similarity Index ◽  
Noise Ratio

DVB merupakan standar transmisi televisi digital yang paling banyak digunakan saat ini. Unsur terpenting dari suatu proses transmisi adalah kualitas gambar dari video yang diterima setelah melalui proses transimisi tersebut. Banyak faktor yang dapat mempengaruhi kualitas dari suatu gambar, salah satunya adalah struktur frame dari video. Pada tulisan ini dilakukan pengujian sensitifitas video MPEG-4 berdasarkan struktur frame pada transmisi DVB-T. Pengujian dilakukan menggunakan simulasi matlab dan simulink. Digunakan juga ffmpeg untuk menyediakan format dan pengaturan video akan disimulasikan. Variabel yang diubah dari video adalah bitrate dan juga group-of-pictures (GOP), sedangkan variabel yang diubah dari transmisi DVB-T adalah signal-to-noise-ratio (SNR) pada kanal AWGN di antara pengirim (Tx) dan penerima (Rx). Hasil yang diperoleh dari percobaan berupa kualitas rata-rata gambar pada video yang diukur menggunakan metode pengukuran structural-similarity-index (SSIM). Dilakukan juga pengukuran terhadap jumlah bit-error-rate BER pada bitstream DVB-T. Percobaan yang dilakukan dapat menunjukkan seberapa besar sensitifitas bitrate dan GOP dari video pada transmisi DVB-T dengan kesimpulan semakin besar bitrate maka akan semakin buruk nilai kualitas gambarnya, dan semakin kecil nilai GOP maka akan semakin baik nilai kualitasnya. Penilitian diharapkan dapat dikembangkan menggunakan deep learning untuk memperoleh frame struktur yang tepat di kondisi-kondisi tertentu dalam proses transmisi televisi digital.

scholarly journals Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5540
Author(s):  
Nayeem Hasan ◽  
Md Saiful Islam ◽  
Wenyu Chen ◽  
Muhammad Ashad Kabir ◽  
Saad Al-Ahmadi
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Reconstructed Image ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Watermarking Scheme

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.

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.

Master Frame Extraction of Fetal Cardiac Images Using B Mode Ultrasound Images

2022 ◽  
Vol 54 ◽  
pp. 51-64
Author(s):  
Sushma Tumkur Venugopal ◽  
Sriraam Natarajan ◽  
Megha P. Arakeri ◽  
Suresh Seshadri
Keyword(s):  
Mean Square Error ◽  
Hausdorff Distance ◽  
Cardiac Cycle ◽  
Fetal Heart ◽  
Fetal Echocardiography ◽  
Similarity Index ◽  
Structural Similarity ◽  
Ultrasound Images ◽  
Mean Square ◽  
Structural Similarity Index

Fetal Echocardiography is used for monitoring the fetal heart and for detection of Congenital Heart Disease (CHD). It is well known that fetal cardiac four chamber view has been widely used for preliminary examination for the detection of CHD. The end diastole frame is generally used for the analysis of the fetal cardiac chambers which is manually picked by the clinician during examination/screening. This method is subjected to intra and inter observer errors and also time consuming. The proposed study aims to automate this process by determining the frame, referred to as the Master frame from the cine loop sequences that can be used for the analysis of the fetal heart chambers instead of the clinically chosen diastole frame. The proposed framework determines the correlation between the reference (first) frame with the successive frames to identify one cardiac cycle. Then the Master frame is formed by superimposing all the frames belonging to one cardiac cycle. The master frame is then compared with the clinically chosen diastole frame in terms of fidelity metrics such as Dice coefficient, Hausdorff distance, mean square error and structural similarity index. The average value of the fidelity metrics considering the dataset used for this study 0.73 for Dice, 13.94 for Hausdorff distance, 0.99 for Structural Similarity Index and 0.035 for mean square error confirms the suitability of the proposed master frame extraction thereby avoiding manual intervention by the clinician. .

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 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.

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