A Parallel Approach For Maximum Quantization Of Descendants Of Wavelet Trees
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 3
Abstract
The Lossless Image Compression Methods Have High Demand, Particularly In A Medical Imaging Systems. Therefore, We Need To Increase The Image Compression Algorithm Acceleration Given The Demand In The Future Than The Present Demand. General Purpose Graphics Processing Unit (Gpgpu) Is An Efficient With The Development Of Computing Technologies. Therefore, The Gpgpu Is Used To Image Compression Algorithms To Achieve Efficiency And Speed In Performance. The Backward Wavelet Tree Based Image Compression Algorithm Uses A Compute Unified Device Architecture (Cuda) Platform For Processing It. After Employing The Dyadic Partition, The Algorithm Constructs The Wavelet Tree And Used To Process In The Backward Manner. However, The Maximum Quantization Of Descendants (Mqd) Is Found In The Tree And It Will Process, With The Only Three Levels Of Mqd’s And The Corresponding Image Coefficients. The Parallel Mqd Algorithm Achieves Acceleration 2.83 Times Faster Than The Serial Mqd And Moreover, As The Image Size Increases, The Algorithm's Speed Improves.
Authors and Affiliations
E. Sudarshan, K. Seena Naik
Keywords
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