Objectness Supervised Merging Algorithm for Color Image Segmentation

Ideal color image segmentation needs both low-level cues and high-level semantic features. This paper proposes a two-hierarchy segmentation model based on merging homogeneous superpixels. First, a region growing strategy is designed for producing homogenous and compact superpixels in different partitions. Total variation smoothing features are adopted in the growing procedure for locating real boundaries. Before merging, we define a combined color-texture histogram feature for superpixels description and, meanwhile, a novel objectness feature is proposed to supervise the region merging procedure for reliable segmentation. Both color-texture histograms and objectness are computed to measure regional similarities between region pairs, and the mixed standard deviation of the union features is exploited to make stop criteria for merging process. Experimental results on the popular benchmark dataset demonstrate the better segmentation performance of the proposed model compared to other well-known segmentation algorithms

Sparse Representation Classification Based on Flexible Patches Sampling of Superpixels for Hyperspectral Images

Aiming at solving the difficulty of modeling on spatial coherence, complete feature extraction, and sparse representation in hyperspectral image classification, a joint sparse representation classification method is investigated by flexible patches sampling of superpixels. First, the principal component analysis and total variation diffusion are employed to form the pseudo color image for simplifying superpixels computing with (simple linear iterative clustering) SLIC model. Then, we design a joint sparse recovery model by sampling overcomplete patches of superpixels to estimate joint sparse characteristics of test pixel, which are carried out on the orthogonal matching pursuit (OMP) algorithm. At last, the pixel is labeled according to the minimum distance constraint for final classification based on the joint sparse coefficients and structured dictionary. Experiments conducted on two real hyperspectral datasets show the superiority and effectiveness of the proposed method