Cellular Automata for Elementary Image Enhancement

@article{Hernndez1996CellularAF,
  title={Cellular Automata for Elementary Image Enhancement},
  author={Gonzalo Hern{\'a}ndez and Hans J. Herrmann},
  journal={CVGIP Graph. Model. Image Process.},
  year={1996},
  volume={58},
  pages={82-89}
}
We study various cellular automata as algorithms for elementary image enhancement, which refers to methods used to improve features of an image without previous information about them that can be implemented by straightforward techniques. Cellular automata appear as natural tools for image processing due to their local nature and simple parallel computer implementation. For this reason various cellular automata algorithms for sharpening and smoothing are presented and studied in this context… 

Figures and Tables from this paper

Cellular automata-based efficient method for the removal of high-density impulsive noise from digital images

This research work presents an efficient algorithm based on two dimensional cellular automata (2D CA), with hybrid rules under null and periodic boundary conditions, for filtering high-density impulsive noise from corrupted digital images.

An effective image noise filtering algorithm using cellular automata

This paper presents image noise filtering based on cellular automata, which can remove impulsive noise from corrupted image and shows significant improvements over the traditional methods of filtering.

Cellular automata as a tool for image processing

An overview is given on the use of cellular automata for image processing, and several schemes are described for automatically learning an appropriate rule set from training data.

Evolutionary Design of Cellular Automata for Noise Reduction of Grayscale Images

A new method to obtain the transition rules of two-dimensional cellular automata that performs grayscale image processing and it is shown that the rule obtained by the proposed method employs symmetry-based strategy in the noise reduction process and this property can reduce complexity of CA.

A Cellular Automaton for Image Compression

Experiments show that this technique has proved to be very efficient for the coding of the smooth texture component in high compression applications using closed lines for the initial set.

A Method of Impulse Noise Reduction from Multi-valued Images Using Cellular Automata

The proposed method of impulse noise reduction from multi-valued images using cellular automata (CA) employs a rule of the detection as a pre-processing to have higher performance for noise reduction than ordinary methods.

A Hybrid Method based on Gas Diffusion Model and Fuzzy Cellular Automata for Image Sharpening

A novel method for image sharpening is presented which is a hybrid of imageSharpening based on Gas Diffusion Model and Fuzzy Cellular Automata which calculates appropriate local value for parameter α in each pixel using fuzzy rules.

Cellular Automata for Medical Image Processing

A number of cellular automata-based algorithms for medical image processing were presented and 2-D mammogram images for the breast cancer diagnosis were investigated.

Spatio-temporal cellular automata-based filtering for image sequence denoising: Application to fluoroscopic sequences

This work presents a novel spatio-temporal cellular automata-based filtering (STCAF) for image sequence denoising using evolutionary methods to obtain the CA set of rules which produces the best possible denoisation under different noise models or/and image sources.
...

References

SHOWING 1-5 OF 5 REFERENCES

Extremal Automata For Image Sharpening

Numerically the parallel iteration of Extremal Rules is studied, on the square lattice with Von Neumann neighborhood and free boundary conditions, the typical transient length, the loss of information and the damage spreading response considering random and smoothening random damage.

Decreasing Energy Functions and Lengths of Transients for Some Cellular Automata

A novel feature of a new "energy funct ion" which does yield a bound for the t rans ient is that it contains not only linea r an d bilinea r ter ms, as is common, but also te rms involving th e minimum function.

Digital Picture Processing

Digital Image Processing, Addison–Wesley, for digital images, SIAM J

  • Algebraic Discrete Methods 6(3), 1985. Reading, MA,
  • 1987