New filtering algorithm based on correlation coefficient model
To remove salt and pepper noise,this paper proposed a new filtering algorithm.The main idea was as follows: First,established a correlation coefficient model based on Euclidean distance.Then,used a critical region to distinguish uncorrupted pixels from corrupted ones.Lastly,searched the most correlated uncorrupted pixels according to correlation coefficient model to restore the corrupted pixels,with the gray value of the uncorrupted ones unchanged.Experimental results indicate that the proposed algorithm is superior to the others in salt and pepper noise denoising.Because of the improvement on traditional operation pattern based on window,this algorithm is even effective in denoising images with salt and pepper noise rate as high as 90%.
This study aims to analyse the spatial characteristics and to draw the declining areas from the whole area of Chung-Cheong Province. For this purpose, the temporal and spatial conditions by the urban decline diagnosis indexes are utilized. Additionally, the spatial autocorrelation method was applied for extraction of those areas. The spatial autocorrelation method is one of the methods on exploring spatial characteristics and considering the spatial factors. We also adopted the concepts of economics and then discovered the characteristics of deprivation areas. In applying this method, the positively valued areas were classified as the complementary areas, and the negatively valued areas as the substitutional areas. The findings show the declining areas and the growing areas caused by the growth of periphery. This study supports the regeneration plan of Chung-Cheong Province in extracting depressed or activated areas and explaining the characteristics of those areas.