Srinivasan Vathsal

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Image denoising is getting more significance, especially in Computed Tomography (CT), which is an important and most common modality in medical imaging. This is mainly due to that the effectiveness of clinical diagnosis using CT image lies on the image quality. The denoising technique for CT images using window-based Multi-wavelet transformation and(More)
Denoising the CT images removes noise from the CT images and so makes the disease diagnosis procedure more efficient. The denoised images have a notable level of raise in its PSNR values, ensuring a smoother image for diagnosis purpose. In the previous work, a CT image denoising technique using window-based Multi-wavelet transformation and thresholding has(More)
The Aim is to HDL Design Implementation of 32×32 Port Wi-Fi Router for Complex NOC Computing Applications like Internet and cloud computing networks. This router is the main component in Network on Chip, the advantage is very simple and reliable for High Speed Parallel Distributed Pipe Line Data Processing Computing technique and very suit for(More)
The Aim is to Implement RTL Design Architecture for Compatible Serial Bit Error Rate Tester SOC& Multi rate Multichannel PRBS Sequence Based SERIAL BERT IP Core for High Speed Wireless Serial Communication Data Acquisition SOC Transceiver Products & Applications (3G, 4G, GPS, GSM, CDMA, WIFI, GIFI etc). Testing of Data Done By Different PRBS Pattern(More)
In this day and age, digital images play a significant role in our day-to-day life. Digital images are utilized in a wide range of fields like medical, business and more. Besides, the digital images play a vital part in the medical field in which it has been utilized to analyze the anatomy. These medical images are used in the identification of different(More)
The inversion of the Radon transform in the presence of noise is numerically unstable in tomographic image reconstruction and is said to be ill conditioned. We propose an efficient hybrid Complex Fourier-Wavelet Regularization (ComForWaRD) that comprises blurring operator inversion followed by noise suppression via scalar shrinkage in both Fourier and(More)
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