Convolution and edge enchancement method of remote sensing ?

Sajan sarthak

1.Convolution filter::- Convolution filter is one of the most commonly used filters in image enhancement in the spatial domain. In convolution filter, the filter mask is called convolution mask or convolution kernel. The convolution kernels are square in shape and are generally of odd number of pixels in size viz., 3x3, 5x5, 7x7 etc. 2.The kernel is moved over the input image for each pixel. A linear transformation function involving the kernel coefficients and the pixel values in the neighborhood selected is used to derive the modified DN of the pixel at the centre of the kernel, in the output image. Each coefficient in the kernel is multiplied by the corresponding DN in the input image, and averaged to derive the modified DN value of the centre pixel... 3.see the example attached then this points. Based on the elements used in the matrix and the procedure used for calculating the new digital number, different digital filters are developed for different purposes. Using different kernels, different type of enhancement can be achieved. For example, high pass and low pass filters are special types of convolution filters, which emphasize the high frequency and low frequency features, respectively. Edge enhancement:::--see the attached file