FeatureJ: Structure

General Description

This plugin enables you to compute, for all elements (pixels/voxels) in an image, the eigenvalues of the so-called structure tensor, which has been used e.g. in texture analysis [1] and image enhancement filtering [2].

Description of Dialog Components

Largest/Middle/Smallest eigenvalue of structure tensor. After computation of the elements of the structure tensor the resulting eigenvalues are ordered for each image element (pixel/voxel). All largest eigenvalues are put in a separate image, as are all smallest (and middle, in 3D). With these options you can choose which of these so-called eigenimages should be displayed by the plugin. Note that due to the positive-semidefiniteness of the structure tensor, the eigenvalues are always larger than or equal to zero. If the size of the image is unity in the z-dimension (single slice), the plugin computes 2D-tensor eigenvalues. Otherwise it computes 3D-tensor eigenvalues. The computations are repeated for every time frame and channel in a 5D image.

Smoothing scale. The smoothing scale is equal to the standard deviation of the Gaussian derivative kernel used in computing the elements of the structure tensor and must be larger than or equal to zero. If you have indicated in the Options dialog that you would like to apply (physically) isotropic Gaussian image smoothing, then in each dimension the scale is divided by the sampling interval in that dimension (that is, the pixel width/height/depth as specified in ImageJ > Image > Properties).

Integration scale. The integration scale is equal to the standard deviation of the Gaussian kernel used in smoothing the elements of the structure tensor and must be larger than or equal to zero. If you have indicated in the Options dialog that you would like to apply (physically) isotropic Gaussian image smoothing, then in each dimension the scale is divided by the sampling interval in that dimension (that is, the "pixel width/height/depth" as specified under ImageJ > Image > Properties).

References