We describe and study geometric properties of discrete circular and spherical means of directional derivatives of functions, as well as discrete approximations of higher order differential operators. For an arbitrary dimension we present a general construction for obtaining discrete spherical means of directional derivatives. The construction is based on using the Minkowski’s existence theorem ...

The world of color image difference modeling can be considered relatively young, when compared with the rich history of general color difference equations. While young, this area of research is well beyond the primordial soup stage. In this paper we present a framework for describing the evolution of color image difference models. This framework builds upon the S-CIELAB model, which in turn was...

Data hiding is the technique of embedding data into video or audio media. With development deep neural networks (DNN), quality images generated by novel methods based on DNN getting better. However, there still room for similarity between original and models which were trained existing frameworks to improve, it hard receiver distinguish whether container image from real sender. We propose a fra...

In recent years, convolutional-neural-network-based methods have been introduced to the field of hyperspectral image super-resolution following their great success in RGB super-resolution. However, images appear different from that they high dimensionality, implying a redundancy high-dimensional space. Existing approaches struggle learning spectral correlation and spatial priors, leading inferi...