Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...

Speckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound image and despeckling is necessary for better diagnosis. The main aim of despeckling is to keep the important features such as edges of the ultrasound image. In this paper an adaptive window hybrid median filter is proposed for despeckling of medical ultrasound images. In the prop...

This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighbouring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighbouring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which cal...

This paper represents a new algorithm which uses a trimmed global mean filter with ROAD to remove random impulse noise. A two step algorithm is implemented in which the first step ensure detection of corrupted pixels in the degraded image and the second step replaces the degraded image with either the median of uncorrupted pixels in the selected window and if the selected window contains noisy ...