Certain applications require the extraction of patches of color from an image, their size and location. These applications may be: color harmonization algorithms, non-photorealistic rendering, etc. These applications use not too big a palette of colors, and in both cases large areas of homogeneous color are favored along with high detail preserved in the smaller areas with a lot of color activi...

self-affine maps were successfully used for edge detection, image segmentation, and contour extraction. they belong to the general category of patch-based methods. particularly, each self-affine map is defined by one pair of patches in the image domain. by minimizing the difference between these patches, the optimal translation vector of the self-affine map is obtained. almost all image process...

This paper presents an algorithm for extracting planar patches by integrating both intensity and range data provided by a stereo system. For dealing with noisy and sparse range data, the initial segmentation is based on intensity information, and then the resulted regions are thresholded using depth data. This new algorithm, different from the existing ones that use only range data in the segme...

Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, we propose a novel sparse coding model based on structural similarity for natural image patch feature extraction. The advantage for our model is to be able to preserve structural information from a scene, which human visual per...

Background: Breast mass is one of the main symptoms breast cancer. Effective and accurate detection masses at an early stage would be great value for clinical cancer analysis. Methods: We developed a novel framework named GFNet. The GFNet comprised three modules, including patch extraction, feature detection. high robustness generality that can self-adapted to images collected by different imag...