Gibbs random field model based weight selection for the 2-D adaptive weighted median filter

Gibbs Random Field Model Based Weight Selection for the 2-D Adaptive Weighted Median Filter

establish electrical connections between components on multilayered circuit boards. Conditions such as excess filling and lack of filling cause electrical defects. The sample shown in Fig. 9 has a cavity, indicating lack of filling. The specular reflectance and variable size of the tungsten particles gives the surface a random texture. In this case, a total of 18 images were taken using stage p...

A Switching Weighted Adaptive Median Filter for Impulse Noise Removal

Images are often corrupted by impulse noise due to a noisy sensor or channel transmission errors. The goal of impulse noise removal is to suppress the noise by preserving the integrity of edges and detail information. In this paper, a new filter called Switching Weighted Adaptive Median (SWAM) filter is proposed for effective suppression of impulse noise which is used to incorporate the Recursi...

An adaptive dynamically weighted median filter for impulse noise removal

A new impulsive noise removal filter, adaptive dynamically weighted median filter (ADWMF), is proposed. A popular method for removing impulsive noise is a median filter whereas the weighted median filter and center weighted median filter were also investigated. ADWMF is based on weighted median filter. In ADWMF, instead of fixed weights, weightages of the filter are dynamically assigned with th...

A Switching Weighted Adaptive Median Filter for Impulse Noise Removal

Modified Directional Weighted Median Filter

Removal of random value impulse noise is essential to help successive process like image segmentation, analysis, pattern recognition etc. To remove uniform/randomvalued impulse noise without compromising the image detail information such as sharp edges, Modified Directional Weighted Median Filter (MDWMF) is proposed. The proposed filter utilizes the second order difference (SOD) along with a th...