- author = "Edwin Roger Banks and Paul Agarwal and Marshall McBride and Claudette Owens",
- title = "Evolving Image Noise Filters through Genetic Programming",
- booktitle = "DoD High Performance Computing Modernization Program Users Group Conference (HPCMP-UGC), 2009",
- year = "2009",
- month = "15-18 " # jun,
- pages = "307--312",
-
abstract = "A form of Evolutionary Computation (EC) called Genetic
Programming (GP) was used to automatically discover
sequences of image noise filters to remove two types of
image noise and a type of communications noise
associated with a remotely sensed imagery. Sensor noise
was modelled by the addition of salt-and-pepper and
grayscale noise to the image. Communication noise was
modeled by inserting a series of blank pixels in
selected image rows to replicate dropped pixel segments
occurring during communication interruptions of
sequential uncompressed image information.
A known image was used for training the evolver. Heavy amounts of noise were added to the known image, and a filter was evolved. (The filtered image was compared to the original with the average image-to-image pixel error establishing the fitness function.). The evolved filter derived for the noisy image was then applied to never-before-seen imagery affected by similar noise conditions to judge the universal applicability of the evolved GP filter. Examples of all described images are included in the presentation.
A variety of image filter primitives were used in this experiment. The evolved sequences of primitives were each then sequentially applied to produce the final filtered image.
These filters were evolved over a typical run length of one week each on a small Linux cluster. Once evolved, the filters were then transported to a PC for application to the never-before-seen images, using an evolve-once, apply-many-times approach. The results of this image filtering experiment were quite dramatic.",
- keywords = "genetic algorithms, genetic programming, Linux cluster, communication interruptions, communications noise, evolutionary computation, grayscale noise, image filtering, image noise filters, remotely sensed imagery, salt-and-pepper noise, sensor noise, sequential uncompressed image information, Linux, filtering theory, image denoising, image resolution, image segmentation, image sequences",
-
DOI = "
doi:10.1109/HPCMP-UGC.2009.50",
- notes = "COLSA Corp., Huntsville, AL, USA Also known as \cite{5729481}",
