Throughout human history, wood has been used for various purposes: for
building shelters, houses and bridges, for manufacturing furniture and
household or agricultural appliances (from ploughs to spoons), as burning
material or simply as walking sticks. Contemporarily, vast amounts of wood
are going into paper production. As a consequence, different qualities of
wood are selected appropriately for the various applications. Beams incorporated
into buildings and constructions have to be sturdy and durable;
boards for furniture are supposed to be free of knots or are expected to have
certain ornamental structures. As long as wood is not simply destined for
burning it should be free of undesired knots or internal damages such as rot
or worm holes. Particularly in cases of infestation with wood destroying
fungi that definitely impairs mechanical strength and even may generate
hollows such damages are frequently invisible from the outside. Radiographic
methods are capable to detect internal damages as well as hidden
knots without the need of drilling holes or cutting a specimen to pieces.
The most thoroughly method to visualise the interior of a wooden specimen
is tomography which shows annual growth rings in their complete circumference
and all the knots or damages that might be included. However, some
of them as well as patterns of annual rings suitable for dendrological investigations
are recognisable with a less laborious method that might be applicable
even in the field, i.e. contemporary digital radiography combined with
image processing. Samples of lumber shall be presented showing the typical
annual ring structures and some infested areas.
An algorithm has been developed to remove reliably dotted interferences impairing the perceptibility of objects within a radiographic image. This particularly is a major challenge encountered with neutron radiographs collected at the NECTAR facility, Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II): the resulting images are dominated by features resembling a snow flurry. These artefacts are caused by scattered neutrons, gamma radiation, cosmic radiation, etc. all hitting the detector CCD directly in spite of a sophisticated shielding. This makes such images rather useless for further direct evaluations.
One approach to resolve this problem of these random effects would be to collect a vast number of single images, to combine them appropriately and to process them with common image filtering procedures. However, it has been shown that, e.g. median filtering, depending on the kernel size in the plane and/or the number of single shots to be combined, is either insufficient or tends to blur sharp lined structures. This inevitably makes a visually controlled processing image by image unavoidable. Particularly in tomographic studies, it would be by far too tedious to treat each single projection by this way. Alternatively, it would be not only more comfortable but also in many cases the only reasonable approach to filter a stack of images in a batch procedure to get rid of the disturbing interferences.
The algorithm presented here meets all these requirements. It reliably frees the images from the snowy pattern described above without the loss of fine structures and without a general blurring of the image. It consists of an iterative, within a batch procedure parameter free filtering algorithm aiming to eliminate the often complex interfering artefacts while leaving the original information untouched as far as possible.