Syed Amjad Ali

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Image denoising is one of the most significant tasks in image processing, analysis and image processing applications. Medical Imaging is one among the emerging application areas where the image denoising plays a vital role. In medical imaging, the acquisition techniques and systems introduce noises and artifacts in the medical image that leads to poor(More)
Heterogeneous computing (HC) systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be inaccuracies in the estimation of task execution times. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that needs to be optimized in such(More)
— 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)
Heterogeneous computing systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be sudden machine failures, higher than expected load, or inaccuracies in estimation of system parameters. Makespan (defined as the completion time for an entire set of tasks) is often the performance(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)
A lot of research work in the image processing has been carried out in the last few years using wavelets. But image denoising has remained a fundamental problem in the field of image processing. The problem of estimating an image that is corrupted by Additive White Gaussian Noise has been of interest for practical and theoretical reasons. Earlier several(More)