Stable Aqueous Suspensions of Manganese Ferrite Clusters with Tunable Nanoscale Dimension and Composition.

Manganese ferrite clusters (MFCs) are spherical assemblies of tens to hundreds of primary nanocrystals whose magnetic properties are valuable in diverse applications. Here we describe how to form these materials in a hydrothermal process that permits the independent control of product cluster size (from 30 to 120 nm) and manganese content of the resulting material. Parameters such as the total amount of water added to the alcoholic reaction media and the ratio of manganese to iron precursor are important factors in achieving multiple types of MFC nanoscale products.

Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset.

Underwater images suffer from color distortion and low contrast, because light is attenuated while it propagates through water. Attenuation under water varies with wavelength, unlike terrestrial images where attenuation is assumed to be spectrally uniform. The attenuation depends both on the water body and the 3D structure of the scene, making color restoration difficult.

Single Image Dehazing Using Haze-Lines.

Haze often limits visibility and reduces contrast in outdoor images. The degradation varies spatially since it depends on the objects' distances from the camera. This dependency is expressed in the transmission coefficients, which control the attenuation.

Best-Buddies Similarity-Robust Template Matching Using Mutual Nearest Neighbors.

We propose a novel method for template matching in unconstrained environments. Its essence is the Best-Buddies Similarity (BBS), a useful, robust, and parameter-free similarity measure between two sets of points. BBS is based on counting the number of Best-Buddies Pairs (BBPs)-pairs of points in source and target sets that are mutual nearest neighbours, i.

Coherency Sensitive Hashing.

Coherency Sensitive Hashing (CSH) extends Locality Sensitivity Hashing (LSH) and PatchMatch to quickly find matching patches between two images. LSH relies on hashing, which maps similar patches to the same bin, in order to find matching patches. PatchMatch, on the other hand, relies on the observation that images are coherent, to propagate good matches to their neighbors in the image plane, using random patch assignment to seed the initial matching.