אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

The K-SVD algorithm is a powerful tool for image denoising but computationally quite intensive. In order to accelerate it we implement the most time consuming parts like sparse coding and assembling the final denoised image vectorized and in parallel on the Cell processor. The Cell processor is a heterogeneous multicore system consisting of a general purpose Power-PC processor unit (PPU) and several fast co-processors, the synergistic processor elements (SPEs). We present runtime results comparing a standard CPU and the Cell implementation and apply the denoising algorithm to CT images. Here, one goal is to estimate the non-gaussian, non-stationary noise in the images and include this information in the K-SVD algorithm.