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## Image profiles and histograms

Visualization of image profiles along an arbitrary line is an invaluable tool to evaluate the presence of artifacts in reconstructed images. For example, in X-ray CT, beam-hardening produces ``cupping'' artifacts that can easily be detected by extracting a profile. Similarly, the accuracy of the reconstruction techniques can be assessed by visualizing the profiles of sharp edges. Typically, low-pass filtering and noise elimination smooth and spread the transitions.

Along the same lines, visualizing a histogram helps understand the statistics of an image and the distribution of its gray levels. In the case where the histogram is made up of several modes, the objects can typicaly be segmented out by applying different thresholdings to the data.

Although most image visualization packages provide 1D signal viewers, our experience proved that they cannot be easily customized by the user and are not flexible enough.

In our applications, the 1D signals are extracted by issuing a command to the pict image widget and sent to a BLT graph. Tcl/Tk handles only character strings and relies on the X protocol to communicate between applications. In addition, the profiles are generally made of less than 1000 samples, so that the overhead introduced by the communications is minimal. This feature allows us to let the user configure the graphical interface. Figure 6 shows an example where a profile is extracted interactively and then sent to a 1D signal viewer. The main benefit of this approach is that the user can dynamically create and extract new profiles or histograms of images viewed across the network, combine and compare them without having to save these one-dimensional signals in files, and transfer them by ftp.