This library provides a C++ class called HSC, which performs feature extraction using the histogram of shearlet coefficients (HSC) method proposed in the paper A Novel Feature Descriptor Based on the Shearlet Transform (ICIP).
Shearlet transformations provide a general framework for analyzing and representing data with anisotropic information at multiple scales. As a consequence, signal singularities, such as edges, can be precisely detected and located in images. Based on the idea of employing histograms to estimate the distribution of edge orientations and on the accurate multi-scale analysis provided by shearlet transformations, we propose a feature descriptor called Histograms of Shearlet Coefficients (HSC).
This code works either on Windows or on Linux and requires OpenCV version 1.0 or superior. In Windows, a project for Visual Studio 2005 is provided. A Makefile can be used to compile all files and generate an executable example, containing an example of usage. To incorporate this library in your project, copy every .cpp and .h file to your directory and compile them with your code. Then, call the methods provided by the class HSC.
The members of the C++ classes and an example regarding how to perform feature extraction using HSC are provided in the documentation manual [pdf]. If you find bugs or problems in this software or you have suggestions to improve or make it more user friendly, please send an e-mail to email@example.com.
This implementation has been used as part of the paper written by Schwartz et al. We kindly ask you to cite the following reference upon the use of this code.
|1.||(2011): A Novel Feature Descriptor Based on the Shearlet Transform. In: IEEE International Conference on Image Processing, pp. 1033-1036, 2011.|