  Sparse decomposition has been extensively used for different applications
including signal compression and denoising and document analysis. In this
paper, sparse decomposition is used for image segmentation. The proposed
algorithm separates the background and foreground using a sparse-smooth
decomposition technique such that the smooth and sparse components correspond
to the background and foreground respectively. This algorithm is tested on
several test images from HEVC test sequences and is shown to have superior
performance over other methods, such as the hierarchical k-means clustering in
DjVu. This segmentation algorithm can also be used for text extraction, video
compression and medical image segmentation.
