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Edge-Preserving Image Filter for Impulsive Noise Removal in Color Images Abstract: Edge-Preserving Image Filter technique intended for impulsive noise removal in color images is presented. The impulsive noise detection algorithm is based on the concept of trimmed cumulated distances, which are assigned to the central pixel of a sliding filtering window. The trimmed sum of distances serves as an indicator of the strength of impulses injected to the image by the impulsive noise process and the restored pixel is obtained as a weighted mean of the processed pixel and the sharpening vector median filter output. Extensive experiments, performed on a set of color test images, proved that the proposed filter is superior to the state-of-the-art impulsive noise reduction algorithms. The new noise filtering design, due to its simple structure and very low computational complexity, can be applied in various applications in which the detail preserving impulsive noise reduction is required. Existing System: SOFT SWITCHING FILTER Disadvantages: Filter applications are limited to real systems. The properties of a little non-Gaussian noise and a little nonlinearity of the system make the filter’s performance very poor. Proposed System: Edge-Preserving Image Filter We consider eight directional differences, from D1 to D8, to reconstruct the noisy pixel value. Only those composed of noise-free pixels are taken into account to avoid possible misdetection. Directions passing through the suspected pixels are discarded to reduce misdetection.

MATLAB projects 2014

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Page 1: MATLAB projects 2014

Edge-Preserving Image Filter for Impulsive Noise Removal in Color Images

Abstract:

Edge-Preserving Image Filter technique intended for impulsive noise removal in

color images is presented. The impulsive noise detection algorithm is based on the

concept of trimmed cumulated distances, which are assigned to the central pixel of a

sliding filtering window. The trimmed sum of distances serves as an indicator of the

strength of impulses injected to the image by the impulsive noise process and the

restored pixel is obtained as a weighted mean of the processed pixel and the

sharpening vector median filter output. Extensive experiments, performed on a set

of color test images, proved that the proposed filter is superior to the state -of-the-art

impulsive noise reduction algorithms. The new noise filtering design, due to its

simple structure and very low computational complexity, can be applied in various

applications in which the detail preserving impulsive noise reduction is required.

Existing System:

SOFT SWITCHING FILTER

Disadvantages:

Filter applications are limited to real systems.

The properties of a little non-Gaussian noise and a little nonlinearity of the system

make the filter’s performance very poor.

Proposed System:

Edge-Preserving Image Filter

We consider eight directional differences, from D1 to D8, to reconstruct the noisy pixel

value. Only those composed of noise-free pixels are taken into account to avoid possible

misdetection. Directions passing through the suspected pixels are discarded to reduce

misdetection.

Page 2: MATLAB projects 2014

Data Flow for Edge-Preserving Image Filter