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We performed a large-scale comparison of full-reference IQA models in terms of their use as objectives for the optimization of image processing algorithms — denoising, deblurring, super-resolution, and compression.

We proposed a Deep Image Structure and Texture Similarity (DISTS) metric, which is sensitive to structural distortions, tolerant of texture resampling, and robust to mild geometric transformations.

We presented a robust active contour model driven by local pre-fitting energy for fast image segmentation.

We proposed an active contour model which combines region-scalable fitting energy and optimized Laplacian of Gaussian energy for image segmentation.

We introduced a novel local intensity fitting energy in active contour models to segment the images with intensity inhomogeneity.